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[GitHub] [incubator-mxnet] ys2843 edited a comment on pull request #18431: [website] Redirect Chinese visitors to Apache Chinese CDN provider PART 1
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[GitHub] [incubator-mxnet] leezu commented on a change in pull request #18403: Gluon.probability
leezu commented on a change in pull request #18403:
URL: https://github.com/apache/incubator-mxnet/pull/18403#discussion_r432805452
##
File path: python/mxnet/gluon/probability/distributions/distribution.py
##
@@ -0,0 +1,196 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements. See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership. The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License. You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied. See the License for the
+# specific language governing permissions and limitations
+# under the License.
+
+# coding: utf-8
+# pylint: disable=wildcard-import
+"""Base distribution class."""
+__all__ = ['Distribution']
+
+from .utils import cached_property
+from numbers import Number
+
+
+class Distribution(object):
+r"""Base class for distribution.
+
+Parameters
+--
+F : mx.ndarray or mx.symbol.numpy._Symbol
+Variable that stores the running mode.
+event_dim : int, default None
+Variable indicating the dimension of the distribution's support.
+validate_args : bool, default None
+Whether to validate the distribution parameters
+"""
+
+# Variable indicating whether the sampling method has
+# pathwise gradient.
+has_grad = False
+support = None
+has_enumerate_support = False
+arg_constraints = {}
+_validate_args = False
+
+@staticmethod
+def set_default_validate_args(value):
+if value not in [True, False]:
+raise ValueError
+Distribution._validate_args = value
+
+def __init__(self, F=None, event_dim=None, validate_args=None):
+self.F = F
Review comment:
Yes. Because eventually we like to refactor the backend and replace the
nnvm representation. The first step is to remove the explicit reference from
the frontend, which implies removing F.
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[GitHub] [incubator-mxnet] xidulu commented on a change in pull request #18403: Gluon.probability
xidulu commented on a change in pull request #18403:
URL: https://github.com/apache/incubator-mxnet/pull/18403#discussion_r432805254
##
File path: python/mxnet/gluon/probability/distributions/distribution.py
##
@@ -0,0 +1,196 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements. See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership. The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License. You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied. See the License for the
+# specific language governing permissions and limitations
+# under the License.
+
+# coding: utf-8
+# pylint: disable=wildcard-import
+"""Base distribution class."""
+__all__ = ['Distribution']
+
+from .utils import cached_property
+from numbers import Number
+
+
+class Distribution(object):
+r"""Base class for distribution.
+
+Parameters
+--
+F : mx.ndarray or mx.symbol.numpy._Symbol
+Variable that stores the running mode.
+event_dim : int, default None
+Variable indicating the dimension of the distribution's support.
+validate_args : bool, default None
+Whether to validate the distribution parameters
+"""
+
+# Variable indicating whether the sampling method has
+# pathwise gradient.
+has_grad = False
+support = None
+has_enumerate_support = False
+arg_constraints = {}
+_validate_args = False
+
+@staticmethod
+def set_default_validate_args(value):
+if value not in [True, False]:
+raise ValueError
+Distribution._validate_args = value
+
+def __init__(self, F=None, event_dim=None, validate_args=None):
+self.F = F
Review comment:
Why is it no longer needed? Do you mean it will be replaced by deferred
computation?
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[GitHub] [incubator-mxnet] xidulu commented on a change in pull request #18403: Gluon.probability
xidulu commented on a change in pull request #18403: URL: https://github.com/apache/incubator-mxnet/pull/18403#discussion_r432805217 ## File path: tests/python/unittest/test_gluon_probability.py ## @@ -0,0 +1,2326 @@ +# Licensed to the Apache Software Foundation (ASF) under one +# or more contributor license agreements. See the NOTICE file +# distributed with this work for additional information +# regarding copyright ownership. The ASF licenses this file +# to you under the Apache License, Version 2.0 (the +# "License"); you may not use this file except in compliance +# with the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, +# software distributed under the License is distributed on an +# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY +# KIND, either express or implied. See the License for the +# specific language governing permissions and limitations +# under the License. + +import os +import tempfile + +import mxnet as mx +from mxnet import np, npx, autograd +from mxnet import gluon +import mxnet.gluon.probability as mgp +from mxnet.gluon.probability import StochasticBlock, StochasticSequential +from mxnet.gluon import HybridBlock +from mxnet.test_utils import use_np, assert_almost_equal, set_default_context +import numpy as _np +from common import (setup_module, with_seed, assertRaises, +assert_raises_cudnn_not_satisfied) +from numpy.testing import assert_array_equal +import pytest +import scipy.stats as ss +import scipy.special as scipy_special +import warnings +import json +import unittest +import random +import itertools +from numbers import Number + +# set_default_context(mx.gpu(0)) + +def prob_to_logit(prob): +return np.log(prob) - np.log1p(-prob) + +def _distribution_method_invoker(dist, func, *args): +"""Wrapper for invoking different types of class methods with one unified +interface. + +Parameters +-- +dist : Distribution +func : method +""" +if (len(args) == 0): +out = getattr(dist, func) +if callable(out): +return out() +else: +return out +return getattr(dist, func)(*args) + + +def test_mgp_getF(): +# Test getF +getF = mgp.utils.getF +nd = mx.nd +sym = mx.sym +assert getF(nd.ones((2,2)), nd.ones((2,2))) == nd +assert getF(sym.ones((2,2)), sym.ones((2,2))) == sym +assert getF(1.0, 2.0) == nd + +# Test exception +try: +getF(nd.ones((2,2)), sym.ones((2,2))) +except TypeError as e: +pass Review comment: You are right, this test is problematic. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[GitHub] [incubator-mxnet] xidulu commented on a change in pull request #18403: Gluon.probability
xidulu commented on a change in pull request #18403:
URL: https://github.com/apache/incubator-mxnet/pull/18403#discussion_r432805167
##
File path: src/operator/random/multisample_op.h
##
@@ -67,7 +67,7 @@ inline bool MultiSampleOpShape(const nnvm::NodeAttrs& attrs,
const MultiSampleParam& param = nnvm::get(attrs.parsed);
mxnet::TShape sshape = param.shape;
for (int i = 0; i < sshape.ndim(); ++i) {
-CHECK_GT(sshape[i], 0) << "shape parameter must be non-zero within each
dimension";
+CHECK_GE(sshape[i], 0) << "shape parameter must be non-zero within each
dimension";
Review comment:
Got that
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[GitHub] [incubator-mxnet] xidulu commented on a change in pull request #18403: Gluon.probability
xidulu commented on a change in pull request #18403: URL: https://github.com/apache/incubator-mxnet/pull/18403#discussion_r432805117 ## File path: tests/python/unittest/test_gluon_probability.py ## @@ -0,0 +1,2326 @@ +# Licensed to the Apache Software Foundation (ASF) under one +# or more contributor license agreements. See the NOTICE file +# distributed with this work for additional information +# regarding copyright ownership. The ASF licenses this file +# to you under the Apache License, Version 2.0 (the +# "License"); you may not use this file except in compliance +# with the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, +# software distributed under the License is distributed on an +# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY +# KIND, either express or implied. See the License for the +# specific language governing permissions and limitations +# under the License. + +import os +import tempfile + +import mxnet as mx +from mxnet import np, npx, autograd +from mxnet import gluon +import mxnet.gluon.probability as mgp +from mxnet.gluon.probability import StochasticBlock, StochasticSequential +from mxnet.gluon import HybridBlock +from mxnet.test_utils import use_np, assert_almost_equal, set_default_context +import numpy as _np +from common import (setup_module, with_seed, assertRaises, +assert_raises_cudnn_not_satisfied) +from numpy.testing import assert_array_equal +import pytest +import scipy.stats as ss +import scipy.special as scipy_special +import warnings +import json +import unittest +import random +import itertools +from numbers import Number + +# set_default_context(mx.gpu(0)) Review comment: Oh, I forgot that, I will change it soon. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[GitHub] [incubator-mxnet] xidulu commented on a change in pull request #18403: Gluon.probability
xidulu commented on a change in pull request #18403: URL: https://github.com/apache/incubator-mxnet/pull/18403#discussion_r432805069 ## File path: python/mxnet/gluon/probability/transformation/transformation.py ## @@ -0,0 +1,289 @@ +# Licensed to the Apache Software Foundation (ASF) under one +# or more contributor license agreements. See the NOTICE file +# distributed with this work for additional information +# regarding copyright ownership. The ASF licenses this file +# to you under the Apache License, Version 2.0 (the +# "License"); you may not use this file except in compliance +# with the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, +# software distributed under the License is distributed on an +# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY +# KIND, either express or implied. See the License for the +# specific language governing permissions and limitations +# under the License. + +# coding: utf-8 +"""Transformation Classes""" +__all__ = ["Transformation", "TransformBlock","ComposeTransform", "ExpTransform", + "AffineTransform", "PowerTransform", "AbsTransform", 'SigmoidTransform', + 'SoftmaxTransform'] + +from ..distributions.utils import _clip_prob, cached_property, sum_right_most +from ...block import HybridBlock +import weakref + + +class Transformation(object): +r"""Abstract class for implementing invertible transformation +with computable log det jacobians + +Attributes +-- +bijective : bool + +""" +bijective = False +event_dim = 0 + +def __init__(self, F=None): +self._inv = None +self._F = F +super(Transformation, self).__init__() + +@property +def F(self): +return self._F + +@F.setter +def F(self, value): +self._F = value + +@property +def sign(self): +""" +Returns the sign of the determinant of the Jacobian. +""" +raise NotImplementedError + +@property +def inv(self): +inv = None +if self._inv is not None: +inv = self._inv() +if inv is None: +inv = _InverseTransformation(self) +self._inv = weakref.ref(inv) +return inv + +def __call__(self, x): +return self._forward_compute(x) + +def _inv_call(self, y): +return self._inverse_compute(y) + +def _forward_compute(self, x): +raise NotImplementedError + +def _inverse_compute(self, x): +raise NotImplementedError + +def log_det_jacobian(self, x, y): +""" +Compute the value of log(|dy/dx|) +""" +raise NotImplementedError + + +class _InverseTransformation(Transformation): +""" +A private class representing the invert of `Transformation`, +which should be accessed through `Transformation.inv` property. +""" +def __init__(self, forward_transformation): +super(_InverseTransformation, self).__init__() +self._inv = forward_transformation + +@property +def inv(self): +return self._inv + +@property +def sign(self): +return self._inv.sign + +@property +def event_dim(self): +return self._inv.event_dim + +def __call__(self, x): +return self._inv._inverse_compute(x) + +def log_det_jacobian(self, x, y): +return -self._inv.log_det_jacobian(y, x) + + +class TransformBlock(Transformation, HybridBlock): Review comment: I did not check whether setting the prefix would have any issues, but the TransformBlock works well, here is an example https://github.com/xidulu/mystery_demo/blob/master/real_nvp.ipynb This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[GitHub] [incubator-mxnet] leezu edited a comment on pull request #18445: updating ubuntu_cpu base image to 20.04 to observe failing tests regarding Python 3.8
leezu edited a comment on pull request #18445: URL: https://github.com/apache/incubator-mxnet/pull/18445#issuecomment-636267475 When updating the base image, the Dockerfile would require some changes. You can test that the containers can still build, locally via: `cd mxnet/ci; DOCKER_CACHE_REGISTRY=mxnetci docker-compose -f docker/docker-compose.yml pull; DOCKER_CACHE_REGISTRY=mxnetci docker-compose -f docker/docker-compose.yml build` This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[GitHub] [incubator-mxnet] leezu commented on pull request #18445: updating ubuntu_cpu base image to 20.04 to observe failing tests regarding Python 3.8
leezu commented on pull request #18445: URL: https://github.com/apache/incubator-mxnet/pull/18445#issuecomment-636267475 When updating the base image, the Dockerfile would require some changes. You can test that the containers can still build, locally via: `DOCKER_CACHE_REGISTRY=mxnetci docker-compose -f docker/docker-compose.yml pull; DOCKER_CACHE_REGISTRY=mxnetci docker-compose -f docker/docker-compose.yml build` This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[incubator-mxnet] branch master updated (5b9aedd -> 2afd66a)
This is an automated email from the ASF dual-hosted git repository. lausen pushed a change to branch master in repository https://gitbox.apache.org/repos/asf/incubator-mxnet.git. from 5b9aedd remove mx.model.FeedForward API (#18394) add 2afd66a CI: Prime docker cache in "Docker cache build" job (#18438) No new revisions were added by this update. Summary of changes: ci/Jenkinsfile_docker_cache | 2 +- ci/jenkins/Jenkins_steps.groovy | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-)
[incubator-mxnet] branch master updated (5b9aedd -> 2afd66a)
This is an automated email from the ASF dual-hosted git repository. lausen pushed a change to branch master in repository https://gitbox.apache.org/repos/asf/incubator-mxnet.git. from 5b9aedd remove mx.model.FeedForward API (#18394) add 2afd66a CI: Prime docker cache in "Docker cache build" job (#18438) No new revisions were added by this update. Summary of changes: ci/Jenkinsfile_docker_cache | 2 +- ci/jenkins/Jenkins_steps.groovy | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-)
[GitHub] [incubator-mxnet] leezu commented on pull request #18391: Disable test_CSVIter
leezu commented on pull request #18391: URL: https://github.com/apache/incubator-mxnet/pull/18391#issuecomment-636266821 @mxnet-bot run ci [miscellaneous] This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[GitHub] [incubator-mxnet] mxnet-bot commented on pull request #18391: Disable test_CSVIter
mxnet-bot commented on pull request #18391: URL: https://github.com/apache/incubator-mxnet/pull/18391#issuecomment-636266830 Jenkins CI successfully triggered : [miscellaneous] This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[incubator-mxnet] branch master updated: CI: Prime docker cache in "Docker cache build" job (#18438)
This is an automated email from the ASF dual-hosted git repository.
lausen pushed a commit to branch master
in repository https://gitbox.apache.org/repos/asf/incubator-mxnet.git
The following commit(s) were added to refs/heads/master by this push:
new 2afd66a CI: Prime docker cache in "Docker cache build" job (#18438)
2afd66a is described below
commit 2afd66af0559d0691b22068d8e3b929d92933cad
Author: Leonard Lausen
AuthorDate: Fri May 29 20:05:31 2020 -0700
CI: Prime docker cache in "Docker cache build" job (#18438)
Cache priming was previously only handled when using the ./ci/build.py or
./ci/docker_cache.py script. The former is used during most CI jobs. The
latter
is used for containers not declared in docker-compose.yml during the "Docker
cache build" job. More and more containers are declared in
docker-compose.yml now, but prior to this commit their cache wasn't primed
in the
"Docker cache build" job.
---
ci/Jenkinsfile_docker_cache | 2 +-
ci/jenkins/Jenkins_steps.groovy | 2 +-
2 files changed, 2 insertions(+), 2 deletions(-)
diff --git a/ci/Jenkinsfile_docker_cache b/ci/Jenkinsfile_docker_cache
index 2bf9040..96cf2c7 100644
--- a/ci/Jenkinsfile_docker_cache
+++ b/ci/Jenkinsfile_docker_cache
@@ -38,7 +38,7 @@ core_logic: {
timeout(time: total_timeout, unit: 'MINUTES') {
utils.init_git()
sh "python3 ./ci/docker_cache.py --docker-registry
${env.DOCKER_CACHE_REGISTRY}"
- sh "cd ci && python3 ./docker_login.py --secret-name
${env.DOCKERHUB_SECRET_NAME} && docker-compose -f docker/docker-compose.yml
build --parallel && COMPOSE_HTTP_TIMEOUT=600 docker-compose -f
docker/docker-compose.yml push && docker logout"
+ sh "cd ci && python3 ./docker_login.py --secret-name
${env.DOCKERHUB_SECRET_NAME} && docker-compose -f docker/docker-compose.yml
pull && docker-compose -f docker/docker-compose.yml build --parallel &&
COMPOSE_HTTP_TIMEOUT=600 docker-compose -f docker/docker-compose.yml push &&
docker logout"
}
}
}
diff --git a/ci/jenkins/Jenkins_steps.groovy b/ci/jenkins/Jenkins_steps.groovy
index 8c8e0da..83b2e01 100644
--- a/ci/jenkins/Jenkins_steps.groovy
+++ b/ci/jenkins/Jenkins_steps.groovy
@@ -1743,7 +1743,7 @@ def misc_test_docker_cache_build() {
ws('workspace/docker_cache') {
utils.init_git()
sh "python3 ./ci/docker_cache.py --docker-registry
${env.DOCKER_CACHE_REGISTRY} --no-publish"
-sh "cd ci && docker-compose -f docker/docker-compose.yml build
--parallel"
+sh "cd ci && docker-compose -f docker/docker-compose.yml pull &&
docker-compose -f docker/docker-compose.yml build --parallel"
}
}
}]
[GitHub] [incubator-mxnet] mxnet-bot commented on pull request #18441: Update nccl installation in Dockerfile.build.centos7
mxnet-bot commented on pull request #18441: URL: https://github.com/apache/incubator-mxnet/pull/18441#issuecomment-636266817 Jenkins CI successfully triggered : [miscellaneous] This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[GitHub] [incubator-mxnet] leezu commented on pull request #18441: Update nccl installation in Dockerfile.build.centos7
leezu commented on pull request #18441: URL: https://github.com/apache/incubator-mxnet/pull/18441#issuecomment-636266807 @mxnet-bot run ci [miscellaneous] This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[GitHub] [incubator-mxnet] leezu merged pull request #18438: CI: Prime docker cache in "Docker cache build" job
leezu merged pull request #18438: URL: https://github.com/apache/incubator-mxnet/pull/18438 This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[GitHub] [incubator-mxnet] ciyongch commented on pull request #18408: Fix CD failure due to illegal instruction in OpenBLAS
ciyongch commented on pull request #18408: URL: https://github.com/apache/incubator-mxnet/pull/18408#issuecomment-636265079 Hi @leezu , can you help to backport this PR to v1.7.x and v1.x as well? Thanks. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[GitHub] [incubator-mxnet] szha commented on pull request #18439: Fix MXNET_PROFILER_MODE doc in env var documentation
szha commented on pull request #18439: URL: https://github.com/apache/incubator-mxnet/pull/18439#issuecomment-636265104 > Thanks for fixing the doc. Profiler is still broken, chrome tracing is not recognizing the json output. How large is the Json dump? This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[GitHub] [incubator-mxnet] ciyongch commented on pull request #18261: [v1.7.x] Backport fixing batch_norm and layer_norm for large tensors (#17805)
ciyongch commented on pull request #18261: URL: https://github.com/apache/incubator-mxnet/pull/18261#issuecomment-636264462 Hi @ChaiBapchya , appreciate for your kindly help, I will give a try in the following day to trigger the nightly build. Will let you know if it works :) This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[GitHub] [incubator-mxnet] mxnet-bot commented on pull request #18445: updating ubuntu_cpu base image to 20.04 to observe failing tests regarding Python 3.8
mxnet-bot commented on pull request #18445: URL: https://github.com/apache/incubator-mxnet/pull/18445#issuecomment-636254155 Hey @ma-hei , Thanks for submitting the PR All tests are already queued to run once. If tests fail, you can trigger one or more tests again with the following commands: - To trigger all jobs: @mxnet-bot run ci [all] - To trigger specific jobs: @mxnet-bot run ci [job1, job2] *** **CI supported jobs**: [edge, unix-cpu, sanity, clang, miscellaneous, centos-gpu, website, windows-gpu, centos-cpu, unix-gpu, windows-cpu] *** _Note_: Only following 3 categories can trigger CI :PR Author, MXNet Committer, Jenkins Admin. All CI tests must pass before the PR can be merged. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[GitHub] [incubator-mxnet] ma-hei opened a new pull request #18445: updating ubuntu_cpu base image to 20.04 to observe failing tests regarding Python 3.8
ma-hei opened a new pull request #18445: URL: https://github.com/apache/incubator-mxnet/pull/18445 ## Description ## This PR is used to observe failing tests when updating ubuntu_cpu base image to 20.04. With ubuntu 20.04 python 3.8 is used. As described in https://github.com/apache/incubator-mxnet/issues/18380 we should observe various test failures. ## Checklist ## ### Essentials ### Please feel free to remove inapplicable items for your PR. - [ ] The PR title starts with [MXNET-$JIRA_ID], where $JIRA_ID refers to the relevant [JIRA issue](https://issues.apache.org/jira/projects/MXNET/issues) created (except PRs with tiny changes) - [ ] Changes are complete (i.e. I finished coding on this PR) - [ ] All changes have test coverage: - Unit tests are added for small changes to verify correctness (e.g. adding a new operator) - Nightly tests are added for complicated/long-running ones (e.g. changing distributed kvstore) - Build tests will be added for build configuration changes (e.g. adding a new build option with NCCL) - [ ] Code is well-documented: - For user-facing API changes, API doc string has been updated. - For new C++ functions in header files, their functionalities and arguments are documented. - For new examples, README.md is added to explain the what the example does, the source of the dataset, expected performance on test set and reference to the original paper if applicable - Check the API doc at https://mxnet-ci-doc.s3-accelerate.dualstack.amazonaws.com/PR-$PR_ID/$BUILD_ID/index.html - [ ] To the best of my knowledge, examples are either not affected by this change, or have been fixed to be compatible with this change ### Changes ### - [ ] Feature1, tests, (and when applicable, API doc) - [ ] Feature2, tests, (and when applicable, API doc) ## Comments ## - If this change is a backward incompatible change, why must this change be made. - Interesting edge cases to note here This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[GitHub] [incubator-mxnet] ma-hei commented on issue #18380: Various issues on Python 3.8
ma-hei commented on issue #18380: URL: https://github.com/apache/incubator-mxnet/issues/18380#issuecomment-636253025 I see, so as part of this fix we would update the base image of ubuntu_cpu to 20.04. I will create a first PR in which the base image of ubuntu_cpu is updated to 20.04, to see which tests are failing. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[GitHub] [incubator-mxnet] leezu edited a comment on issue #18380: Various issues on Python 3.8
leezu edited a comment on issue #18380: URL: https://github.com/apache/incubator-mxnet/issues/18380#issuecomment-636249229 Yes. You'll see an exception due to accessing an undefined function. Though note that you should use pytest instead of nosetest. For the tests, only `tests/python/unittest/test_profiler.py` is affected by the `time.clock` issue. But there may be more issues. To enforce that there are no remaining issues, eventually we should switch the Ubuntu CI to Python 3.8 and ensure that all tests pass (at which stage the PR can be merged). This can be achieved by switching https://github.com/apache/incubator-mxnet/blob/master/ci/docker/Dockerfile.build.ubuntu to Ubuntu 20.04, as 20.04 ships with Python 3.8 by default. The base image for above dockerifle is specified in https://github.com/apache/incubator-mxnet/blob/master/ci/docker/docker-compose.yml Currently there are no nvidia cuda images based on 20.04 yet. So when updating the CPU image to 20.04, the GPU images would need to remain on 18.04. Switching the CI can be done separately from fixing the bugs. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[GitHub] [incubator-mxnet] leezu edited a comment on issue #18380: Various issues on Python 3.8
leezu edited a comment on issue #18380: URL: https://github.com/apache/incubator-mxnet/issues/18380#issuecomment-636249229 Yes. You'll see an exception due to accessing an undefined function. Though note that you should use pytest instead of nosetest. For the tests, only `tests/python/unittest/test_profiler.py` is affected by the `time.clock` issue. But there may be more issues. So the best solution is to switch the Ubuntu CI to Python 3.8 and ensure that all tests pass (at which stage the PR can be merged). This can be achieved by switching https://github.com/apache/incubator-mxnet/blob/master/ci/docker/Dockerfile.build.ubuntu to Ubuntu 20.04, as 20.04 ships with Python 3.8 by default. The base image for above dockerifle is specified in https://github.com/apache/incubator-mxnet/blob/master/ci/docker/docker-compose.yml Currently there are no nvidia cuda images based on 20.04 yet. So when updating the CPU image to 20.04, the GPU images would need to remain on 18.04. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[GitHub] [incubator-mxnet] leezu edited a comment on issue #18380: Various issues on Python 3.8
leezu edited a comment on issue #18380: URL: https://github.com/apache/incubator-mxnet/issues/18380#issuecomment-636249229 Yes. You'll see an exception due to accessing an undefined function. Though note that you should use pytest instead of nosetest. For the tests, only `tests/python/unittest/test_profiler.py` is affected by the `time.clock` issue. But there may be more issues. So the best solution is to switch the Ubuntu CI to Python 3.8 and ensure that all tests pass (at which stage the PR can be merged). This can be achieved by switching https://github.com/apache/incubator-mxnet/blob/master/ci/docker/Dockerfile.build.ubuntu to Ubuntu 20.04, as 20.04 ships with Python 3.8 by default. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[incubator-mxnet-site] branch asf-site updated: Bump the publish timestamp.
This is an automated email from the ASF dual-hosted git repository. aaronmarkham pushed a commit to branch asf-site in repository https://gitbox.apache.org/repos/asf/incubator-mxnet-site.git The following commit(s) were added to refs/heads/asf-site by this push: new 799ec59 Bump the publish timestamp. 799ec59 is described below commit 799ec59148ad63268cdf3a473a7f9f5b728418e8 Author: mxnet-ci AuthorDate: Sat May 30 00:48:27 2020 + Bump the publish timestamp. --- date.txt | 1 + 1 file changed, 1 insertion(+) diff --git a/date.txt b/date.txt new file mode 100644 index 000..d075ad2 --- /dev/null +++ b/date.txt @@ -0,0 +1 @@ +Sat May 30 00:48:27 UTC 2020
[GitHub] [incubator-mxnet] leezu commented on issue #18380: Various issues on Python 3.8
leezu commented on issue #18380: URL: https://github.com/apache/incubator-mxnet/issues/18380#issuecomment-636249229 Yes. You'll see an exception due to accessing an undefined function. Though note that you should use pytest instead of nosetest. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[GitHub] [incubator-mxnet] ma-hei commented on issue #18380: Various issues on Python 3.8
ma-hei commented on issue #18380: URL: https://github.com/apache/incubator-mxnet/issues/18380#issuecomment-636248939 @leezu can this be reproduced locally by running python tests via nosetest? This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[GitHub] [incubator-mxnet] mxnet-bot commented on pull request #18444: More clear description to `transform_first`
mxnet-bot commented on pull request #18444: URL: https://github.com/apache/incubator-mxnet/pull/18444#issuecomment-636247939 Hey @goldmermaid , Thanks for submitting the PR All tests are already queued to run once. If tests fail, you can trigger one or more tests again with the following commands: - To trigger all jobs: @mxnet-bot run ci [all] - To trigger specific jobs: @mxnet-bot run ci [job1, job2] *** **CI supported jobs**: [edge, clang, unix-gpu, website, windows-gpu, windows-cpu, centos-cpu, sanity, miscellaneous, unix-cpu, centos-gpu] *** _Note_: Only following 3 categories can trigger CI :PR Author, MXNet Committer, Jenkins Admin. All CI tests must pass before the PR can be merged. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[GitHub] [incubator-mxnet] goldmermaid opened a new pull request #18444: More clear description to `transform_first`
goldmermaid opened a new pull request #18444: URL: https://github.com/apache/incubator-mxnet/pull/18444 After teaching an MLU-CV class, some students feel confused when they are using the `transform_first` function. So I modified it a bit to make it more clear. :) This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[incubator-mxnet] branch v1.x updated: Fix PyPI Packages and Python Docker Images nightly release (#18222) (#18432)
This is an automated email from the ASF dual-hosted git repository.
lausen pushed a commit to branch v1.x
in repository https://gitbox.apache.org/repos/asf/incubator-mxnet.git
The following commit(s) were added to refs/heads/v1.x by this push:
new 3ee8e00 Fix PyPI Packages and Python Docker Images nightly release
(#18222) (#18432)
3ee8e00 is described below
commit 3ee8e00292a2ea70f1c6885c318af688b1d1c3c5
Author: Lin Yuan
AuthorDate: Fri May 29 16:43:38 2020 -0700
Fix PyPI Packages and Python Docker Images nightly release (#18222) (#18432)
* remove OS from s3 library path
* fix bash script run commands
* Revert "remove OS from s3 library path"
This reverts commit 266511305ba1ac56582ee9b867d0a64ad3d60378.
* hardcode s3 path for upload/download of binaries
Co-authored-by: Ubuntu
Co-authored-by: Manu Seth <22492939+mset...@users.noreply.github.com>
Co-authored-by: Ubuntu
---
cd/Jenkinsfile_utils.groovy | 4 ++--
1 file changed, 2 insertions(+), 2 deletions(-)
diff --git a/cd/Jenkinsfile_utils.groovy b/cd/Jenkinsfile_utils.groovy
index 966f0a2..cfda3ad 100644
--- a/cd/Jenkinsfile_utils.groovy
+++ b/cd/Jenkinsfile_utils.groovy
@@ -116,12 +116,12 @@ def push_artifact(libmxnet_path, variant, libtype,
license_paths = '', dependenc
if(license_paths == null) license_paths = ''
if(dependency_paths == null) dependency_paths = ''
- sh "./cd/utils/artifact_repository.py --push --verbose --libtype ${libtype}
--variant ${variant} --libmxnet ${libmxnet_path} --licenses ${license_paths}
--dependencies ${dependency_paths}"
+ sh "./cd/utils/artifact_repository.py --push --verbose --libtype ${libtype}
--variant ${variant} --libmxnet ${libmxnet_path} --licenses ${license_paths}
--dependencies ${dependency_paths} --os ubuntu18.04"
}
// pull artifact from repository
def pull_artifact(variant, libtype, destination = '') {
- sh "./cd/utils/artifact_repository.py --pull --verbose --libtype ${libtype}
--variant ${variant} --destination ${destination}"
+ sh "./cd/utils/artifact_repository.py --pull --verbose --libtype ${libtype}
--variant ${variant} --destination ${destination} --os ubuntu18.04"
}
// pulls artifact from repository and places files in the appropriate
directories
[incubator-mxnet] branch v1.x updated: Fix PyPI Packages and Python Docker Images nightly release (#18222) (#18432)
This is an automated email from the ASF dual-hosted git repository.
lausen pushed a commit to branch v1.x
in repository https://gitbox.apache.org/repos/asf/incubator-mxnet.git
The following commit(s) were added to refs/heads/v1.x by this push:
new 3ee8e00 Fix PyPI Packages and Python Docker Images nightly release
(#18222) (#18432)
3ee8e00 is described below
commit 3ee8e00292a2ea70f1c6885c318af688b1d1c3c5
Author: Lin Yuan
AuthorDate: Fri May 29 16:43:38 2020 -0700
Fix PyPI Packages and Python Docker Images nightly release (#18222) (#18432)
* remove OS from s3 library path
* fix bash script run commands
* Revert "remove OS from s3 library path"
This reverts commit 266511305ba1ac56582ee9b867d0a64ad3d60378.
* hardcode s3 path for upload/download of binaries
Co-authored-by: Ubuntu
Co-authored-by: Manu Seth <22492939+mset...@users.noreply.github.com>
Co-authored-by: Ubuntu
---
cd/Jenkinsfile_utils.groovy | 4 ++--
1 file changed, 2 insertions(+), 2 deletions(-)
diff --git a/cd/Jenkinsfile_utils.groovy b/cd/Jenkinsfile_utils.groovy
index 966f0a2..cfda3ad 100644
--- a/cd/Jenkinsfile_utils.groovy
+++ b/cd/Jenkinsfile_utils.groovy
@@ -116,12 +116,12 @@ def push_artifact(libmxnet_path, variant, libtype,
license_paths = '', dependenc
if(license_paths == null) license_paths = ''
if(dependency_paths == null) dependency_paths = ''
- sh "./cd/utils/artifact_repository.py --push --verbose --libtype ${libtype}
--variant ${variant} --libmxnet ${libmxnet_path} --licenses ${license_paths}
--dependencies ${dependency_paths}"
+ sh "./cd/utils/artifact_repository.py --push --verbose --libtype ${libtype}
--variant ${variant} --libmxnet ${libmxnet_path} --licenses ${license_paths}
--dependencies ${dependency_paths} --os ubuntu18.04"
}
// pull artifact from repository
def pull_artifact(variant, libtype, destination = '') {
- sh "./cd/utils/artifact_repository.py --pull --verbose --libtype ${libtype}
--variant ${variant} --destination ${destination}"
+ sh "./cd/utils/artifact_repository.py --pull --verbose --libtype ${libtype}
--variant ${variant} --destination ${destination} --os ubuntu18.04"
}
// pulls artifact from repository and places files in the appropriate
directories
[GitHub] [incubator-mxnet] leezu merged pull request #18432: [v1.x] Backport: Fix PyPI Packages and Python Docker Images nightly release (#18222)
leezu merged pull request #18432: URL: https://github.com/apache/incubator-mxnet/pull/18432 This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[GitHub] [incubator-mxnet] leezu commented on pull request #18443: Disable test coverage in MKL builds
leezu commented on pull request #18443: URL: https://github.com/apache/incubator-mxnet/pull/18443#issuecomment-636235953 The stability problem I observed seems unrelated (https://github.com/apache/incubator-mxnet/issues/18442). However, disabling the test coverage at this point is a low-hanging fruit to improve the CI: MKL tests take 3h+ whereas all other tests take <1h. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[GitHub] [incubator-mxnet] marcoabreu commented on pull request #18443: Disable test coverage in MKL builds
marcoabreu commented on pull request #18443: URL: https://github.com/apache/incubator-mxnet/pull/18443#issuecomment-636233684 The issue is talking about speed but you're talking about stability. Are the test coverage injection causing instability? This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[GitHub] [incubator-mxnet] leezu commented on pull request #18443: Disable test coverage in MKL builds
leezu commented on pull request #18443: URL: https://github.com/apache/incubator-mxnet/pull/18443#issuecomment-636233246 I agree with you that this solution shouldn't be the final solution. However, currently the MKL tests are quite unstable on CI. @bgawrych is looking into it. Until we have a proper solution, I suggest to disable the test coverage for MKL builds to make the CI more stable. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[GitHub] [incubator-mxnet] marcoabreu commented on pull request #18443: Disable test coverage in MKL builds
marcoabreu commented on pull request #18443: URL: https://github.com/apache/incubator-mxnet/pull/18443#issuecomment-636231308 It is expected that test coverage recording introduces slow down. Especially since core logic is run on the cpu for mkl while for GPU the core logic is run on GPU. I'd rather exclude the mkl core package from test coverage than disabling it entirely. For this, I'd recommend looking at where most CPU time is spent. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[GitHub] [incubator-mxnet] mxnet-bot commented on pull request #18391: Disable test_CSVIter
mxnet-bot commented on pull request #18391: URL: https://github.com/apache/incubator-mxnet/pull/18391#issuecomment-636230865 Jenkins CI successfully triggered : [unix-cpu, miscellaneous] This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[GitHub] [incubator-mxnet] leezu commented on pull request #18391: Disable test_CSVIter
leezu commented on pull request #18391: URL: https://github.com/apache/incubator-mxnet/pull/18391#issuecomment-636230830 @mxnet-bot run ci [unix-cpu, miscellaneous] This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[GitHub] [incubator-mxnet] leezu commented on pull request #18438: CI: Prime docker cache in "Docker cache build" job
leezu commented on pull request #18438: URL: https://github.com/apache/incubator-mxnet/pull/18438#issuecomment-636230644 @mxnet-bot run ci [unix-cpu] This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[GitHub] [incubator-mxnet] mxnet-bot commented on pull request #18438: CI: Prime docker cache in "Docker cache build" job
mxnet-bot commented on pull request #18438: URL: https://github.com/apache/incubator-mxnet/pull/18438#issuecomment-636230676 Jenkins CI successfully triggered : [unix-cpu] This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[GitHub] [incubator-mxnet] mxnet-bot commented on pull request #18443: Disable test coverage in MKL builds
mxnet-bot commented on pull request #18443: URL: https://github.com/apache/incubator-mxnet/pull/18443#issuecomment-636230314 Hey @leezu , Thanks for submitting the PR All tests are already queued to run once. If tests fail, you can trigger one or more tests again with the following commands: - To trigger all jobs: @mxnet-bot run ci [all] - To trigger specific jobs: @mxnet-bot run ci [job1, job2] *** **CI supported jobs**: [centos-gpu, unix-gpu, windows-cpu, website, windows-gpu, unix-cpu, sanity, clang, miscellaneous, edge, centos-cpu] *** _Note_: Only following 3 categories can trigger CI :PR Author, MXNet Committer, Jenkins Admin. All CI tests must pass before the PR can be merged. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[GitHub] [incubator-mxnet] leezu opened a new pull request #18443: Disable test coverage in MKL builds
leezu opened a new pull request #18443: URL: https://github.com/apache/incubator-mxnet/pull/18443 Reference: https://github.com/apache/incubator-mxnet/issues/18244#issuecomment-635911844 cc: @bgawrych This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[GitHub] [incubator-mxnet] leezu opened a new issue #18442: CI: MKLDNN-MKL-CPU tests hang during test collection stage
leezu opened a new issue #18442: URL: https://github.com/apache/incubator-mxnet/issues/18442 ## Description ``` [2020-05-29T18:49:28.268Z] + pytest --durations=50 --cov-report xml:tests_unittest.xml --verbose tests/python/unittest [2020-05-29T18:49:31.528Z] = test session starts == [2020-05-29T18:49:31.528Z] platform linux -- Python 3.6.9, pytest-5.3.5, py-1.8.1, pluggy-0.13.1 -- /usr/bin/python3 [2020-05-29T18:49:31.528Z] cachedir: .pytest_cache [2020-05-29T18:49:31.528Z] rootdir: /work/mxnet, inifile: pytest.ini [2020-05-29T18:49:31.528Z] plugins: flaky-3.6.1, xdist-1.31.0, timeout-1.3.4, cov-2.8.1, env-0.6.2, forked-1.1.3 [2020-05-29T18:49:31.528Z] timeout: 1200.0s [2020-05-29T18:49:31.528Z] timeout method: signal [2020-05-29T18:49:31.528Z] timeout func_only: False [2020-05-29T22:44:00.825Z] Sending interrupt signal to process ``` http://jenkins.mxnet-ci.amazon-ml.com/blue/organizations/jenkins/mxnet-validation%2Funix-cpu/detail/PR-18391/1/pipeline/366 Maybe related https://github.com/apache/incubator-mxnet/issues/18244 cc: @bgawrych This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[GitHub] [incubator-mxnet] ChaiBapchya commented on pull request #18261: [v1.7.x] Backport fixing batch_norm and layer_norm for large tensors (#17805)
ChaiBapchya commented on pull request #18261: URL: https://github.com/apache/incubator-mxnet/pull/18261#issuecomment-636229346 @TaoLv is a committer and Committers can trigger pipelines on Jenkins. @ciyongch I've given "ciyonch" access to trigger jobs as well. Pl confirm. Hope that helps. Thanks. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[GitHub] [incubator-mxnet] ChaiBapchya commented on pull request #18261: [v1.7.x] Backport fixing batch_norm and layer_norm for large tensors (#17805)
ChaiBapchya commented on pull request #18261: URL: https://github.com/apache/incubator-mxnet/pull/18261#issuecomment-636227822 Triggered NightlyTests and NightlyTestsForBinaries for v1.7.x This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[GitHub] [incubator-mxnet] mxnet-bot commented on pull request #18441: Update nccl installation in Dockerfile.build.centos7
mxnet-bot commented on pull request #18441: URL: https://github.com/apache/incubator-mxnet/pull/18441#issuecomment-636226990 Hey @leezu , Thanks for submitting the PR All tests are already queued to run once. If tests fail, you can trigger one or more tests again with the following commands: - To trigger all jobs: @mxnet-bot run ci [all] - To trigger specific jobs: @mxnet-bot run ci [job1, job2] *** **CI supported jobs**: [sanity, windows-gpu, unix-gpu, centos-cpu, miscellaneous, clang, website, edge, windows-cpu, centos-gpu, unix-cpu] *** _Note_: Only following 3 categories can trigger CI :PR Author, MXNet Committer, Jenkins Admin. All CI tests must pass before the PR can be merged. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[GitHub] [incubator-mxnet] leezu opened a new pull request #18441: Update nccl installation in Dockerfile.build.centos7
leezu opened a new pull request #18441: URL: https://github.com/apache/incubator-mxnet/pull/18441 By moving the NCCL installation before the `COPY runtime_functions.sh` statement, users will not suffer from cache invalidation due to the COPY and don't have to repeat the nccl installation locally as there will be a cache hit when using `python ci/build.py --platform centos7_gpu_cu100 /work/runtime_functions.sh build_static_libmxnet cu100`. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[GitHub] [incubator-mxnet] mseth10 commented on pull request #18434: add image classification tutorial for jetson
mseth10 commented on pull request #18434: URL: https://github.com/apache/incubator-mxnet/pull/18434#issuecomment-636224207 @samskalicky thanks for the review. I have addressed your comments. Can you give it another pass? Thanks! This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[GitHub] [incubator-mxnet] mxnet-bot commented on pull request #18385: Safe accumulation for computing gradient in Embedding & Take
mxnet-bot commented on pull request #18385: URL: https://github.com/apache/incubator-mxnet/pull/18385#issuecomment-636222498 Jenkins CI successfully triggered : [miscellaneous] This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[GitHub] [incubator-mxnet] MoisesHer commented on pull request #18385: Safe accumulation for computing gradient in Embedding & Take
MoisesHer commented on pull request #18385: URL: https://github.com/apache/incubator-mxnet/pull/18385#issuecomment-636222460 @mxnet-bot run ci [miscellaneous] This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[GitHub] [incubator-mxnet] mxnet-bot commented on pull request #18440: Fix backward of scalar variants of arctan2 and rarctan2 on GPU
mxnet-bot commented on pull request #18440: URL: https://github.com/apache/incubator-mxnet/pull/18440#issuecomment-636213233 Hey @ptrendx , Thanks for submitting the PR All tests are already queued to run once. If tests fail, you can trigger one or more tests again with the following commands: - To trigger all jobs: @mxnet-bot run ci [all] - To trigger specific jobs: @mxnet-bot run ci [job1, job2] *** **CI supported jobs**: [centos-gpu, edge, website, clang, windows-gpu, unix-gpu, unix-cpu, centos-cpu, sanity, windows-cpu, miscellaneous] *** _Note_: Only following 3 categories can trigger CI :PR Author, MXNet Committer, Jenkins Admin. All CI tests must pass before the PR can be merged. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[GitHub] [incubator-mxnet] ptrendx opened a new pull request #18440: Fix backward of scalar variants of arctan2 and rarctan2 on GPU
ptrendx opened a new pull request #18440: URL: https://github.com/apache/incubator-mxnet/pull/18440 ## Description ## The used BinaryScalarOp::Compute instead of BinaryScalarOp::Backward. CPU version is using the proper function. It seems there are no tests for `_scalar` versions of NumPy operators, FYI @haojin2 @sxjscience This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[incubator-mxnet] branch v1.x updated: Revert PR 17767 for fixing GPU memory usage regression (#18283) (#18309)
This is an automated email from the ASF dual-hosted git repository.
haibin pushed a commit to branch v1.x
in repository https://gitbox.apache.org/repos/asf/incubator-mxnet.git
The following commit(s) were added to refs/heads/v1.x by this push:
new d621e50 Revert PR 17767 for fixing GPU memory usage regression
(#18283) (#18309)
d621e50 is described below
commit d621e50862a96d259135fcfac0098f7709ee0f00
Author: Ziyi Mu
AuthorDate: Fri May 29 14:51:17 2020 -0700
Revert PR 17767 for fixing GPU memory usage regression (#18283) (#18309)
* Revert "Fix and optimize handling of vectorized memory accesses (#17767)"
This reverts commit 5542d03695b4a2589afb88acf128d4ba8ac94d0d.
* add license to reverted file
---
3rdparty/mshadow/mshadow/base.h| 48 +++
3rdparty/mshadow/mshadow/half2.h | 162 +++
src/common/cuda_vectorization.cuh | 283 --
src/operator/mshadow_op.h | 67 +
src/operator/tensor/elemwise_binary_op.cuh | 322 -
src/operator/tensor/elemwise_binary_op.h | 206 ++---
src/operator/tensor/elemwise_binary_op_basic.cu| 23 +-
src/operator/tensor/elemwise_binary_scalar_op.cuh | 207 -
src/operator/tensor/elemwise_binary_scalar_op.h| 75 +
.../tensor/elemwise_binary_scalar_op_basic.cu | 9 +-
.../tensor/elemwise_binary_scalar_op_extended.cu | 15 +-
src/operator/tensor/elemwise_sum.cu| 112 +--
src/operator/tensor/elemwise_sum.h | 12 +
src/operator/tensor/elemwise_unary_op.cuh | 127
src/operator/tensor/elemwise_unary_op.h| 56 ++--
src/operator/tensor/elemwise_unary_op_basic.cu | 1 -
src/operator/tensor/elemwise_unary_op_pow.cu | 1 -
src/operator/tensor/elemwise_unary_op_trig.cu | 1 -
tests/python/unittest/test_operator.py | 81 +-
19 files changed, 464 insertions(+), 1344 deletions(-)
diff --git a/3rdparty/mshadow/mshadow/base.h b/3rdparty/mshadow/mshadow/base.h
index 6469bbc..9f53857 100755
--- a/3rdparty/mshadow/mshadow/base.h
+++ b/3rdparty/mshadow/mshadow/base.h
@@ -295,6 +295,7 @@ extern "C" {
}
#include "./half.h"
+#include "./half2.h"
#include "./bfloat.h"
#define MSHADOW_HALF_BF_OPERATOR(RTYPE, OP)
\
MSHADOW_XINLINE RTYPE operator OP(mshadow::half::half_t a,
mshadow::bfloat::bf16_t b) { \
@@ -409,6 +410,11 @@ struct DataType {
#endif
};
template<>
+struct DataType {
+ static const int kFlag = kFloat16;
+ static const int kLanes = 2;
+};
+template<>
struct DataType {
static const int kFlag = kBfloat16;
static const int kLanes = 1;
@@ -1161,6 +1167,48 @@ struct minimum {
}
#endif
+#define MSHADOW_TYPE_SWITCH_WITH_HALF2(type, DType, ...) \
+ switch (type) { \
+ case mshadow::kFloat32: \
+{ \
+ typedef float DType;\
+ {__VA_ARGS__} \
+} \
+break;\
+ case mshadow::kFloat64: \
+{ \
+ typedef double DType; \
+ {__VA_ARGS__} \
+} \
+break;\
+ case mshadow::kFloat16: \
+{ \
+ typedef mshadow::half::half2_t DType; \
+ {__VA_ARGS__} \
+} \
+break;\
+ case mshadow::kUint8: \
+{ \
+ typedef uint8_t DType; \
+ {__VA_ARGS__} \
+} \
+break;\
+ case mshadow::kInt32: \
+{ \
+ typedef int32_t DType; \
+ {__VA_ARGS__} \
+} \
+break;\
+ case mshadow::kInt64: \
+{ \
+ typedef int64_t DType; \
+
[incubator-mxnet] branch v1.x updated: Revert PR 17767 for fixing GPU memory usage regression (#18283) (#18309)
This is an automated email from the ASF dual-hosted git repository.
haibin pushed a commit to branch v1.x
in repository https://gitbox.apache.org/repos/asf/incubator-mxnet.git
The following commit(s) were added to refs/heads/v1.x by this push:
new d621e50 Revert PR 17767 for fixing GPU memory usage regression
(#18283) (#18309)
d621e50 is described below
commit d621e50862a96d259135fcfac0098f7709ee0f00
Author: Ziyi Mu
AuthorDate: Fri May 29 14:51:17 2020 -0700
Revert PR 17767 for fixing GPU memory usage regression (#18283) (#18309)
* Revert "Fix and optimize handling of vectorized memory accesses (#17767)"
This reverts commit 5542d03695b4a2589afb88acf128d4ba8ac94d0d.
* add license to reverted file
---
3rdparty/mshadow/mshadow/base.h| 48 +++
3rdparty/mshadow/mshadow/half2.h | 162 +++
src/common/cuda_vectorization.cuh | 283 --
src/operator/mshadow_op.h | 67 +
src/operator/tensor/elemwise_binary_op.cuh | 322 -
src/operator/tensor/elemwise_binary_op.h | 206 ++---
src/operator/tensor/elemwise_binary_op_basic.cu| 23 +-
src/operator/tensor/elemwise_binary_scalar_op.cuh | 207 -
src/operator/tensor/elemwise_binary_scalar_op.h| 75 +
.../tensor/elemwise_binary_scalar_op_basic.cu | 9 +-
.../tensor/elemwise_binary_scalar_op_extended.cu | 15 +-
src/operator/tensor/elemwise_sum.cu| 112 +--
src/operator/tensor/elemwise_sum.h | 12 +
src/operator/tensor/elemwise_unary_op.cuh | 127
src/operator/tensor/elemwise_unary_op.h| 56 ++--
src/operator/tensor/elemwise_unary_op_basic.cu | 1 -
src/operator/tensor/elemwise_unary_op_pow.cu | 1 -
src/operator/tensor/elemwise_unary_op_trig.cu | 1 -
tests/python/unittest/test_operator.py | 81 +-
19 files changed, 464 insertions(+), 1344 deletions(-)
diff --git a/3rdparty/mshadow/mshadow/base.h b/3rdparty/mshadow/mshadow/base.h
index 6469bbc..9f53857 100755
--- a/3rdparty/mshadow/mshadow/base.h
+++ b/3rdparty/mshadow/mshadow/base.h
@@ -295,6 +295,7 @@ extern "C" {
}
#include "./half.h"
+#include "./half2.h"
#include "./bfloat.h"
#define MSHADOW_HALF_BF_OPERATOR(RTYPE, OP)
\
MSHADOW_XINLINE RTYPE operator OP(mshadow::half::half_t a,
mshadow::bfloat::bf16_t b) { \
@@ -409,6 +410,11 @@ struct DataType {
#endif
};
template<>
+struct DataType {
+ static const int kFlag = kFloat16;
+ static const int kLanes = 2;
+};
+template<>
struct DataType {
static const int kFlag = kBfloat16;
static const int kLanes = 1;
@@ -1161,6 +1167,48 @@ struct minimum {
}
#endif
+#define MSHADOW_TYPE_SWITCH_WITH_HALF2(type, DType, ...) \
+ switch (type) { \
+ case mshadow::kFloat32: \
+{ \
+ typedef float DType;\
+ {__VA_ARGS__} \
+} \
+break;\
+ case mshadow::kFloat64: \
+{ \
+ typedef double DType; \
+ {__VA_ARGS__} \
+} \
+break;\
+ case mshadow::kFloat16: \
+{ \
+ typedef mshadow::half::half2_t DType; \
+ {__VA_ARGS__} \
+} \
+break;\
+ case mshadow::kUint8: \
+{ \
+ typedef uint8_t DType; \
+ {__VA_ARGS__} \
+} \
+break;\
+ case mshadow::kInt32: \
+{ \
+ typedef int32_t DType; \
+ {__VA_ARGS__} \
+} \
+break;\
+ case mshadow::kInt64: \
+{ \
+ typedef int64_t DType; \
+
[incubator-mxnet] branch v1.x updated: Revert PR 17767 for fixing GPU memory usage regression (#18283) (#18309)
This is an automated email from the ASF dual-hosted git repository.
haibin pushed a commit to branch v1.x
in repository https://gitbox.apache.org/repos/asf/incubator-mxnet.git
The following commit(s) were added to refs/heads/v1.x by this push:
new d621e50 Revert PR 17767 for fixing GPU memory usage regression
(#18283) (#18309)
d621e50 is described below
commit d621e50862a96d259135fcfac0098f7709ee0f00
Author: Ziyi Mu
AuthorDate: Fri May 29 14:51:17 2020 -0700
Revert PR 17767 for fixing GPU memory usage regression (#18283) (#18309)
* Revert "Fix and optimize handling of vectorized memory accesses (#17767)"
This reverts commit 5542d03695b4a2589afb88acf128d4ba8ac94d0d.
* add license to reverted file
---
3rdparty/mshadow/mshadow/base.h| 48 +++
3rdparty/mshadow/mshadow/half2.h | 162 +++
src/common/cuda_vectorization.cuh | 283 --
src/operator/mshadow_op.h | 67 +
src/operator/tensor/elemwise_binary_op.cuh | 322 -
src/operator/tensor/elemwise_binary_op.h | 206 ++---
src/operator/tensor/elemwise_binary_op_basic.cu| 23 +-
src/operator/tensor/elemwise_binary_scalar_op.cuh | 207 -
src/operator/tensor/elemwise_binary_scalar_op.h| 75 +
.../tensor/elemwise_binary_scalar_op_basic.cu | 9 +-
.../tensor/elemwise_binary_scalar_op_extended.cu | 15 +-
src/operator/tensor/elemwise_sum.cu| 112 +--
src/operator/tensor/elemwise_sum.h | 12 +
src/operator/tensor/elemwise_unary_op.cuh | 127
src/operator/tensor/elemwise_unary_op.h| 56 ++--
src/operator/tensor/elemwise_unary_op_basic.cu | 1 -
src/operator/tensor/elemwise_unary_op_pow.cu | 1 -
src/operator/tensor/elemwise_unary_op_trig.cu | 1 -
tests/python/unittest/test_operator.py | 81 +-
19 files changed, 464 insertions(+), 1344 deletions(-)
diff --git a/3rdparty/mshadow/mshadow/base.h b/3rdparty/mshadow/mshadow/base.h
index 6469bbc..9f53857 100755
--- a/3rdparty/mshadow/mshadow/base.h
+++ b/3rdparty/mshadow/mshadow/base.h
@@ -295,6 +295,7 @@ extern "C" {
}
#include "./half.h"
+#include "./half2.h"
#include "./bfloat.h"
#define MSHADOW_HALF_BF_OPERATOR(RTYPE, OP)
\
MSHADOW_XINLINE RTYPE operator OP(mshadow::half::half_t a,
mshadow::bfloat::bf16_t b) { \
@@ -409,6 +410,11 @@ struct DataType {
#endif
};
template<>
+struct DataType {
+ static const int kFlag = kFloat16;
+ static const int kLanes = 2;
+};
+template<>
struct DataType {
static const int kFlag = kBfloat16;
static const int kLanes = 1;
@@ -1161,6 +1167,48 @@ struct minimum {
}
#endif
+#define MSHADOW_TYPE_SWITCH_WITH_HALF2(type, DType, ...) \
+ switch (type) { \
+ case mshadow::kFloat32: \
+{ \
+ typedef float DType;\
+ {__VA_ARGS__} \
+} \
+break;\
+ case mshadow::kFloat64: \
+{ \
+ typedef double DType; \
+ {__VA_ARGS__} \
+} \
+break;\
+ case mshadow::kFloat16: \
+{ \
+ typedef mshadow::half::half2_t DType; \
+ {__VA_ARGS__} \
+} \
+break;\
+ case mshadow::kUint8: \
+{ \
+ typedef uint8_t DType; \
+ {__VA_ARGS__} \
+} \
+break;\
+ case mshadow::kInt32: \
+{ \
+ typedef int32_t DType; \
+ {__VA_ARGS__} \
+} \
+break;\
+ case mshadow::kInt64: \
+{ \
+ typedef int64_t DType; \
+
[GitHub] [incubator-mxnet] eric-haibin-lin merged pull request #18309: [1.x] Revert PR 17767 for fixing GPU memory usage regression (#18283)
eric-haibin-lin merged pull request #18309: URL: https://github.com/apache/incubator-mxnet/pull/18309 This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[GitHub] [incubator-mxnet] mseth10 commented on a change in pull request #18434: add image classification tutorial for jetson
mseth10 commented on a change in pull request #18434: URL: https://github.com/apache/incubator-mxnet/pull/18434#discussion_r432640363 ## File path: docs/python_docs/python/tutorials/deploy/inference/image_classification_jetson.md ## @@ -0,0 +1,130 @@ + + + + + + + + + + + + + + + + + +# Image Classication using pretrained ResNet-50 model on Jetson module Review comment: This tutorial has been tested on the two Jetson modules - Nano and Xavier AGX. I'll specify the device names to be more specific. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[GitHub] [incubator-mxnet] mseth10 commented on a change in pull request #18434: add image classification tutorial for jetson
mseth10 commented on a change in pull request #18434:
URL: https://github.com/apache/incubator-mxnet/pull/18434#discussion_r432744191
##
File path:
docs/python_docs/python/tutorials/deploy/inference/image_classification_jetson.md
##
@@ -0,0 +1,130 @@
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+# Image Classication using pretrained ResNet-50 model on Jetson module
+
+This tutorial shows how to install latest MXNet v1.6 with Jetson support and
use it to deploy a pre-trained MXNet model for image classification on a Jetson
module.
+
+## What's in this tutorial?
+
+This tutorial shows how to:
+
+1. Install MXNet v1.6 with Jetson support along with its dependencies
+
+2. Deploy a pre-trained MXNet model for image classifcation on a Jetson module
+
+### Who's this tutorial for?
+
+This tutorial would benefit developers working on any Jetson module
implementing a deep learning application. It assumes that readers have a Jetson
module setup, are familiar with the Jetson working environment and are somewhat
familiar with deep learning using MXNet.
+
+### How to use this tutorial?
+
+To follow this tutorial, you need to setup a [Jetson
module](https://developer.nvidia.com/embedded/develop/hardware) and install
latest [Jetpack 4.4](https://docs.nvidia.com/jetson/jetpack/release-notes/)
using NVIDIA [SDK manager](https://developer.nvidia.com/nvidia-sdk-manager).
+
+All instructions described in this tutorial can be executed on the any Jetson
module directly or via SSH.
+
+## Prerequisites
+
+To complete this tutorial, you will need:
+
+* A Jetson module with Jetpack 4.4 installed
+* [Swapfile](https://help.ubuntu.com/community/SwapFaq) installed (in case of
Jetson Nano) for additional memory
+
+## Installing MXNet v1.6 with Jetson support
+
+We start by installing MXNet dependencies
+```bash
+sudo apt-get update
+sudo apt-get install -y git build-essential libopenblas-dev libopencv-dev
python3-pip
+sudo pip3 install -U pip
+```
+
+Then we download and install MXNet v1.6 wheel with Jetson support
+```bash
+wget
https://mxnet-public.s3.us-east-2.amazonaws.com/install/jetson/1.6.0/mxnet_cu102-1.6.0-py2.py3-none-linux_aarch64.whl
+sudo pip3 install mxnet_cu102-1.6.0-py2.py3-none-linux_aarch64.whl
+```
+
+And we are done. You can test the installation now by importing mxnet from
python3
+```bash
+>>> python3 -c 'import mxnet'
+```
+
+## Running a pre-trained ResNet-50 model on Jetson
+
+We are now ready to run a pre-trained model and run inference on a Jetson
module. In this tutorial we are using ResNet-50 model trained on Imagenet
dataset. We run the following classification script with either cpu/gpu context
using python3.
+
+```python
+from mxnet.gluon import nn
+import mxnet as mx
+import numpy as np
+import urllib.request
+import cv2
+
+# set context
+ctx = mx.gpu()
+dtype = 'float32'
+bsize = 1
+
+# download model files
+path = 'http://data.mxnet.io/models/imagenet/'
+symbol,_ =
urllib.request.urlretrieve(path+'resnet/50-layers/resnet-50-symbol.json')
+params,_ =
urllib.request.urlretrieve(path+'resnet/50-layers/resnet-50-.params')
+label_file,_ = urllib.request.urlretrieve(path+'synset.txt')
+
+# load model
+input_names = ['data', 'softmax_label']
+net = nn.SymbolBlock.imports(symbol, input_names, params, ctx)
+net.cast(dtype)
+net.hybridize(static_alloc=True, static_shape=True)
+
+# load labels
+with open(label_file, 'r') as f:
+labels = [l.rstrip() for l in f]
+
+# load image
+img_file,_ =
urllib.request.urlretrieve('https://github.com/dmlc/web-data/blob/master/mxnet/doc/tutorials/python/predict_image/cat.jpg?raw=true')
+img = cv2.imread(img_file)
+img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
+img = cv2.resize(img, (224, 224,))
+img = np.swapaxes(img, 0, 2)
+img = np.swapaxes(img, 1, 2)
+
+# format input
+batch = mx.nd.zeros((bsize,) + img.shape)
+for i in range(bsize):
+batch[i] = img
+inputs = batch.astype(dtype)
+mx_img = [mx.nd.array(inputs,ctx), mx.nd.zeros((bsize,),ctx)]
Review comment:
We need not pass the second parameter anyway. I'll remove it.
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[GitHub] [incubator-mxnet] ys2843 commented on pull request #18431: [website] Redirect Chinese visitors to Apache Chinese CDN provider PART 1
ys2843 commented on pull request #18431: URL: https://github.com/apache/incubator-mxnet/pull/18431#issuecomment-636196866 > Just checked with a tool and the results are as follows: > > Original website: https://www.dotcom-tools.com/website-speed-test.aspx#2D4761ACDB144D809F0E16105FC25827 > CDN website: https://www.dotcom-tools.com/website-speed-test.aspx#D08B03A9E383480C926C9946A86F6956 > > Generally, the original website is more consistent. The CDN has higher loading time on first as well as second visit. > > Of course this would need more thorough inspection, but from the first look it seems like we should only use the CDN when there'a a specific issue we identified. > > Before taking such drastic steps I'd appreciate some A/B testing or further inspection before simply moving all users to a different host. Apache servers are in our control but others might not. Agreed, > @ys2843 please make sure to discuss topics (like generally considering a move to a CDN) on dev@ before reaching out to Apache Infra. Yes, sure. This should be further discussed within the team before moving on. Currently fixing the website in China is what this project primarily aims. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[GitHub] [incubator-mxnet] marcoabreu commented on pull request #18431: [website] Redirect Chinese visitors to Apache Chinese CDN provider PART 1
marcoabreu commented on pull request #18431: URL: https://github.com/apache/incubator-mxnet/pull/18431#issuecomment-636193776 https://developers.google.com/speed/pagespeed/insights/?hl=en=https%3A%2F%2Fmxnet.apache.org%2F https://developers.google.com/speed/pagespeed/insights/?url=https%3A%2F%2Fmxnet.cdn.apache.org%2F You might also want to check out speed insights from google. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[GitHub] [incubator-mxnet] marcoabreu commented on pull request #18431: [website] Redirect Chinese visitors to Apache Chinese CDN provider PART 1
marcoabreu commented on pull request #18431: URL: https://github.com/apache/incubator-mxnet/pull/18431#issuecomment-636194055 @ys2843 please make sure to discuss topics (like generally considering a move to a CDN) on dev@ before reaching out to Apache Infra. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[GitHub] [incubator-mxnet] marcoabreu edited a comment on pull request #18431: [website] Redirect Chinese visitors to Apache Chinese CDN provider PART 1
marcoabreu edited a comment on pull request #18431: URL: https://github.com/apache/incubator-mxnet/pull/18431#issuecomment-636191705 Just checked with a tool and the results are as follows: Original website: https://www.dotcom-tools.com/website-speed-test.aspx#2D4761ACDB144D809F0E16105FC25827 CDN website: https://www.dotcom-tools.com/website-speed-test.aspx#D08B03A9E383480C926C9946A86F6956 Generally, the original website is more consistent. The CDN has higher loading time on first as well as second visit. Of course this would need more thorough inspection, but from the first look it seems like we should only use the CDN when there'a a specific issue we identified. Before taking such drastic steps I'd appreciate some A/B testing or further inspection before simply moving all users to a different host. Apache servers are in our control but others might not. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[GitHub] [incubator-mxnet] marcoabreu commented on pull request #18431: [website] Redirect Chinese visitors to Apache Chinese CDN provider PART 1
marcoabreu commented on pull request #18431: URL: https://github.com/apache/incubator-mxnet/pull/18431#issuecomment-636191705 Just checked with a tool and the results are as follows: Original website: https://www.dotcom-tools.com/website-speed-test.aspx#2D4761ACDB144D809F0E16105FC25827 CDN website: https://www.dotcom-tools.com/website-speed-test.aspx#D08B03A9E383480C926C9946A86F6956 Generally, the original website is more consistent. The CDN has higher loading time on first as well as second visit. Of course this would need more thorough inspection, but from the first look it seems like we should only use the CDN when there'a a specific issue we identified. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[GitHub] [incubator-mxnet] ys2843 commented on pull request #18431: [website] Redirect Chinese visitors to Apache Chinese CDN provider PART 1
ys2843 commented on pull request #18431: URL: https://github.com/apache/incubator-mxnet/pull/18431#issuecomment-636189548 > This is great. Anecdotally, the cdn is faster for me and I'm in California. Maybe we should just use the CDN for all traffic? We heard from another community member in Australia that the site is slow there too... wdyt? Yeah, I will reach out to Apache to get more info about this, whether it is allowed to redirect more/all users to this CDN, or if they can point official website ip to it. But I guess it will take some time to address this issue, while this is a Chinese CDN provider that might be out of Apache's control. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[incubator-mxnet] branch v1.x updated: [1.x] Pass args fix2 (#18236)
This is an automated email from the ASF dual-hosted git repository.
apeforest pushed a commit to branch v1.x
in repository https://gitbox.apache.org/repos/asf/incubator-mxnet.git
The following commit(s) were added to refs/heads/v1.x by this push:
new ac3e71b [1.x] Pass args fix2 (#18236)
ac3e71b is described below
commit ac3e71b2ae0d39a9b4af4c047decc2e4a28e759a
Author: Sam Skalicky
AuthorDate: Fri May 29 13:50:02 2020 -0700
[1.x] Pass args fix2 (#18236)
* fixed overwrite of args/aux variables
* fixed spacing
* Merged #18177
* updated python RPM URL
---
python/mxnet/symbol/symbol.py | 16
1 file changed, 8 insertions(+), 8 deletions(-)
diff --git a/python/mxnet/symbol/symbol.py b/python/mxnet/symbol/symbol.py
index 37b9186..e90fb9b 100644
--- a/python/mxnet/symbol/symbol.py
+++ b/python/mxnet/symbol/symbol.py
@@ -1484,18 +1484,18 @@ class Symbol(SymbolBase):
assert isinstance(backend, str)
if args is None or len(args) == 0:
-args = []
+args_ = []
args_handle = c_array(NDArrayHandle, [])
else:
-args_handle, args = self._get_ndarray_inputs('args', args,
-
self.list_arguments(), False)
+args_handle, args_ = self._get_ndarray_inputs('args', args,
+
self.list_arguments(), False)
if aux is None or len(aux) == 0:
-aux = []
+aux_ = []
aux_handle = c_array(NDArrayHandle, [])
else:
-aux_handle, aux = self._get_ndarray_inputs('aux_states', aux,
-
self.list_auxiliary_states(), False)
+aux_handle, aux_ = self._get_ndarray_inputs('aux_states', aux,
+
self.list_auxiliary_states(), False)
if ctx is None:
ctx = current_context()
assert isinstance(ctx, Context)
@@ -1516,9 +1516,9 @@ class Symbol(SymbolBase):
c_str(backend),
ctypes.c_int(ctx.device_typeid),
ctypes.byref(out),
- mx_uint(len(args)),
+ mx_uint(len(args_)),
args_handle,
- mx_uint(len(aux)),
+ mx_uint(len(aux_)),
aux_handle,
mx_uint(len(key_list)),
c_str_array(key_list),
[incubator-mxnet] branch v1.x updated: [1.x] Pass args fix2 (#18236)
This is an automated email from the ASF dual-hosted git repository.
apeforest pushed a commit to branch v1.x
in repository https://gitbox.apache.org/repos/asf/incubator-mxnet.git
The following commit(s) were added to refs/heads/v1.x by this push:
new ac3e71b [1.x] Pass args fix2 (#18236)
ac3e71b is described below
commit ac3e71b2ae0d39a9b4af4c047decc2e4a28e759a
Author: Sam Skalicky
AuthorDate: Fri May 29 13:50:02 2020 -0700
[1.x] Pass args fix2 (#18236)
* fixed overwrite of args/aux variables
* fixed spacing
* Merged #18177
* updated python RPM URL
---
python/mxnet/symbol/symbol.py | 16
1 file changed, 8 insertions(+), 8 deletions(-)
diff --git a/python/mxnet/symbol/symbol.py b/python/mxnet/symbol/symbol.py
index 37b9186..e90fb9b 100644
--- a/python/mxnet/symbol/symbol.py
+++ b/python/mxnet/symbol/symbol.py
@@ -1484,18 +1484,18 @@ class Symbol(SymbolBase):
assert isinstance(backend, str)
if args is None or len(args) == 0:
-args = []
+args_ = []
args_handle = c_array(NDArrayHandle, [])
else:
-args_handle, args = self._get_ndarray_inputs('args', args,
-
self.list_arguments(), False)
+args_handle, args_ = self._get_ndarray_inputs('args', args,
+
self.list_arguments(), False)
if aux is None or len(aux) == 0:
-aux = []
+aux_ = []
aux_handle = c_array(NDArrayHandle, [])
else:
-aux_handle, aux = self._get_ndarray_inputs('aux_states', aux,
-
self.list_auxiliary_states(), False)
+aux_handle, aux_ = self._get_ndarray_inputs('aux_states', aux,
+
self.list_auxiliary_states(), False)
if ctx is None:
ctx = current_context()
assert isinstance(ctx, Context)
@@ -1516,9 +1516,9 @@ class Symbol(SymbolBase):
c_str(backend),
ctypes.c_int(ctx.device_typeid),
ctypes.byref(out),
- mx_uint(len(args)),
+ mx_uint(len(args_)),
args_handle,
- mx_uint(len(aux)),
+ mx_uint(len(aux_)),
aux_handle,
mx_uint(len(key_list)),
c_str_array(key_list),
[GitHub] [incubator-mxnet] apeforest merged pull request #18236: [1.x] Pass args fix2
apeforest merged pull request #18236: URL: https://github.com/apache/incubator-mxnet/pull/18236 This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[GitHub] [incubator-mxnet] anirudh2290 opened a new pull request #18439: Fix MXNET_PROFILER_MODE doc in env var documentation
anirudh2290 opened a new pull request #18439: URL: https://github.com/apache/incubator-mxnet/pull/18439 ## Description ## Fix MXNET_PROFILER_MODE doc in env var documentation ## Checklist ## ### Essentials ### Please feel free to remove inapplicable items for your PR. - [ ] The PR title starts with [MXNET-$JIRA_ID], where $JIRA_ID refers to the relevant [JIRA issue](https://issues.apache.org/jira/projects/MXNET/issues) created (except PRs with tiny changes) - [ ] Changes are complete (i.e. I finished coding on this PR) - [ ] All changes have test coverage: - Unit tests are added for small changes to verify correctness (e.g. adding a new operator) - Nightly tests are added for complicated/long-running ones (e.g. changing distributed kvstore) - Build tests will be added for build configuration changes (e.g. adding a new build option with NCCL) - [ ] Code is well-documented: - For user-facing API changes, API doc string has been updated. - For new C++ functions in header files, their functionalities and arguments are documented. - For new examples, README.md is added to explain the what the example does, the source of the dataset, expected performance on test set and reference to the original paper if applicable - Check the API doc at https://mxnet-ci-doc.s3-accelerate.dualstack.amazonaws.com/PR-$PR_ID/$BUILD_ID/index.html - [ ] To the best of my knowledge, examples are either not affected by this change, or have been fixed to be compatible with this change ### Changes ### - [ ] Feature1, tests, (and when applicable, API doc) - [ ] Feature2, tests, (and when applicable, API doc) ## Comments ## - If this change is a backward incompatible change, why must this change be made. - Interesting edge cases to note here This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[GitHub] [incubator-mxnet] mxnet-bot commented on pull request #18439: Fix MXNET_PROFILER_MODE doc in env var documentation
mxnet-bot commented on pull request #18439: URL: https://github.com/apache/incubator-mxnet/pull/18439#issuecomment-636155967 Hey @anirudh2290 , Thanks for submitting the PR All tests are already queued to run once. If tests fail, you can trigger one or more tests again with the following commands: - To trigger all jobs: @mxnet-bot run ci [all] - To trigger specific jobs: @mxnet-bot run ci [job1, job2] *** **CI supported jobs**: [edge, clang, sanity, windows-gpu, centos-gpu, windows-cpu, miscellaneous, centos-cpu, website, unix-gpu, unix-cpu] *** _Note_: Only following 3 categories can trigger CI :PR Author, MXNet Committer, Jenkins Admin. All CI tests must pass before the PR can be merged. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[GitHub] [incubator-mxnet] leezu commented on a change in pull request #18403: Gluon.probability
leezu commented on a change in pull request #18403: URL: https://github.com/apache/incubator-mxnet/pull/18403#discussion_r432683605 ## File path: python/mxnet/gluon/probability/block/stochastic_block.py ## @@ -0,0 +1,130 @@ +# Licensed to the Apache Software Foundation (ASF) under one +# or more contributor license agreements. See the NOTICE file +# distributed with this work for additional information +# regarding copyright ownership. The ASF licenses this file +# to you under the Apache License, Version 2.0 (the +# "License"); you may not use this file except in compliance +# with the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, +# software distributed under the License is distributed on an +# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY +# KIND, either express or implied. See the License for the +# specific language governing permissions and limitations +# under the License. + +# coding: utf-8 +# pylint: disable=wildcard-import +"""Stochastic block class.""" +__all__ = ['StochasticBlock', 'StochasticSequential'] + +from functools import wraps +from ...block import HybridBlock +from ...nn.basic_layers import HybridSequential +from ...utils import _indent + + +class StochasticBlock(HybridBlock): +"""`StochasticBlock` extends `HybridBlock` to support accumulating loss +in the forward phase, which is extremely useful in building Bayesian Neural Network, +where the loss function is composed of a classification loss and a KL loss. + +""" + +def __init__(self, prefix=None, params=None): +super(StochasticBlock, self).__init__(prefix=prefix, params=params) +self._losses = [] +self._losscache = [] +self._count = 0 + +def add_loss(self, loss): +self._count += 1 +self._losscache.append(loss) + +@staticmethod +def collectLoss(func): +"""To accumulate loss during the forward phase, one could first decorate +hybrid_forward with `StochasticBlock.collectLos`s`, +and then collect the loss tensor `x` by calling self.add_loss(x). +For example, in the following forward function, +we generate samples from a Gaussian parameterized by `loc` and `scale` and +accumulate the KL-divergence between it and its prior into the block's loss storage.: +@StochasticBlock.collectLoss +def hybrid_forward(self, F, loc, scale): +qz = mgp.Normal(loc, scale) +# prior +pz = mgp.Normal(F.np.zeros_like(loc), F.np.ones_like(scale)) +self.add_loss(mgp.kl_divergence(qz, pz)) +return qz.sample() +""" +@wraps(func) +def inner(self, *args, **kwargs): +# Loss from hybrid_forward +func_out = func(self, *args, **kwargs) +collected_loss = self._losscache +self._losscache = [] +return (func_out, collected_loss) + +return inner + +def __call__(self, *args): +"""Calls forward. Only accepts positional arguments.""" +for hook in self._forward_pre_hooks.values(): +hook(self, args) +self._losses = [] +out = self.forward(*args) # out[0]: net output, out[1]: collected loss +self._losses.extend(out[1]) +for hook in self._forward_hooks.values(): +hook(self, args, out) +return out[0] + +@property +def losses(self): +return self._losses + + +class StochasticSequential(StochasticBlock): +"""Stack StochasticBlock sequentially. +""" + +def __init__(self, prefix=None, params=None): +super(StochasticSequential, self).__init__( +prefix=prefix, params=params) +self._layers = [] + +def add(self, *blocks): +"""Adds block on top of the stack.""" +for block in blocks: +self._layers.append(block) +self.register_child(block) + +@StochasticBlock.collectLoss +def hybrid_forward(self, F, x): +for block in self._layers: +x = block(x) Review comment: For the `hybrid_forward` API, it seems you forgot to use `F` here? ## File path: python/mxnet/gluon/probability/block/stochastic_block.py ## @@ -0,0 +1,130 @@ +# Licensed to the Apache Software Foundation (ASF) under one +# or more contributor license agreements. See the NOTICE file +# distributed with this work for additional information +# regarding copyright ownership. The ASF licenses this file +# to you under the Apache License, Version 2.0 (the +# "License"); you may not use this file except in compliance +# with the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, +# software distributed under the License is distributed on an +# "AS IS"
[GitHub] [incubator-mxnet] leezu commented on issue #18436: import mxnet gives error : Illegal instruction (core dumped)
leezu commented on issue #18436: URL: https://github.com/apache/incubator-mxnet/issues/18436#issuecomment-636137376 Currently you need to build from source. It'll take a bit more time to fix the Pypi wheels This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[incubator-mxnet-site] branch asf-site updated: Bump the publish timestamp.
This is an automated email from the ASF dual-hosted git repository. aaronmarkham pushed a commit to branch asf-site in repository https://gitbox.apache.org/repos/asf/incubator-mxnet-site.git The following commit(s) were added to refs/heads/asf-site by this push: new ac39f37 Bump the publish timestamp. ac39f37 is described below commit ac39f37d8f506525f28e0e74ca5940b811ea670f Author: mxnet-ci AuthorDate: Fri May 29 18:48:15 2020 + Bump the publish timestamp. --- date.txt | 1 + 1 file changed, 1 insertion(+) diff --git a/date.txt b/date.txt new file mode 100644 index 000..8395cf8 --- /dev/null +++ b/date.txt @@ -0,0 +1 @@ +Fri May 29 18:48:15 UTC 2020
[GitHub] [incubator-mxnet] leezu opened a new pull request #18438: CI: Prime docker cache in "Docker cache build" job
leezu opened a new pull request #18438: URL: https://github.com/apache/incubator-mxnet/pull/18438 Cache priming was previously only handled when using the ./ci/build.py or ./ci/docker_cache.py script. The former is used during most CI jobs. The latter is used for containers not declared in docker-compose.yml during the "Docker cache build" job. As more and more containers are declared in docker-compose.yml, we need to fix the cache priming issue. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[GitHub] [incubator-mxnet] mxnet-bot commented on pull request #18438: CI: Prime docker cache in "Docker cache build" job
mxnet-bot commented on pull request #18438: URL: https://github.com/apache/incubator-mxnet/pull/18438#issuecomment-636124736 Hey @leezu , Thanks for submitting the PR All tests are already queued to run once. If tests fail, you can trigger one or more tests again with the following commands: - To trigger all jobs: @mxnet-bot run ci [all] - To trigger specific jobs: @mxnet-bot run ci [job1, job2] *** **CI supported jobs**: [clang, windows-cpu, centos-cpu, edge, unix-cpu, miscellaneous, sanity, website, centos-gpu, unix-gpu, windows-gpu] *** _Note_: Only following 3 categories can trigger CI :PR Author, MXNet Committer, Jenkins Admin. All CI tests must pass before the PR can be merged. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[GitHub] [incubator-mxnet] mseth10 commented on a change in pull request #18434: add image classification tutorial for jetson
mseth10 commented on a change in pull request #18434:
URL: https://github.com/apache/incubator-mxnet/pull/18434#discussion_r432660822
##
File path:
docs/python_docs/python/tutorials/deploy/inference/image_classification_jetson.md
##
@@ -0,0 +1,130 @@
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+# Image Classication using pretrained ResNet-50 model on Jetson module
+
+This tutorial shows how to install latest MXNet v1.6 with Jetson support and
use it to deploy a pre-trained MXNet model for image classification on a Jetson
module.
+
+## What's in this tutorial?
+
+This tutorial shows how to:
+
+1. Install MXNet v1.6 with Jetson support along with its dependencies
+
+2. Deploy a pre-trained MXNet model for image classifcation on a Jetson module
+
+### Who's this tutorial for?
+
+This tutorial would benefit developers working on any Jetson module
implementing a deep learning application. It assumes that readers have a Jetson
module setup, are familiar with the Jetson working environment and are somewhat
familiar with deep learning using MXNet.
+
+### How to use this tutorial?
+
+To follow this tutorial, you need to setup a [Jetson
module](https://developer.nvidia.com/embedded/develop/hardware) and install
latest [Jetpack 4.4](https://docs.nvidia.com/jetson/jetpack/release-notes/)
using NVIDIA [SDK manager](https://developer.nvidia.com/nvidia-sdk-manager).
+
+All instructions described in this tutorial can be executed on the any Jetson
module directly or via SSH.
+
+## Prerequisites
+
+To complete this tutorial, you will need:
+
+* A Jetson module with Jetpack 4.4 installed
+* [Swapfile](https://help.ubuntu.com/community/SwapFaq) installed (in case of
Jetson Nano) for additional memory
+
+## Installing MXNet v1.6 with Jetson support
+
+We start by installing MXNet dependencies
+```bash
+sudo apt-get update
+sudo apt-get install -y git build-essential libopenblas-dev libopencv-dev
python3-pip
+sudo pip3 install -U pip
+```
+
+Then we download and install MXNet v1.6 wheel with Jetson support
+```bash
+wget
https://mxnet-public.s3.us-east-2.amazonaws.com/install/jetson/1.6.0/mxnet_cu102-1.6.0-py2.py3-none-linux_aarch64.whl
+sudo pip3 install mxnet_cu102-1.6.0-py2.py3-none-linux_aarch64.whl
+```
+
+And we are done. You can test the installation now by importing mxnet from
python3
+```bash
+>>> python3 -c 'import mxnet'
+```
+
+## Running a pre-trained ResNet-50 model on Jetson
+
+We are now ready to run a pre-trained model and run inference on a Jetson
module. In this tutorial we are using ResNet-50 model trained on Imagenet
dataset. We run the following classification script with either cpu/gpu context
using python3.
+
+```python
+from mxnet.gluon import nn
+import mxnet as mx
+import numpy as np
+import urllib.request
+import cv2
+
+# set context
+ctx = mx.gpu()
+dtype = 'float32'
+bsize = 1
+
+# download model files
+path = 'http://data.mxnet.io/models/imagenet/'
+symbol,_ =
urllib.request.urlretrieve(path+'resnet/50-layers/resnet-50-symbol.json')
+params,_ =
urllib.request.urlretrieve(path+'resnet/50-layers/resnet-50-.params')
+label_file,_ = urllib.request.urlretrieve(path+'synset.txt')
+
+# load model
+input_names = ['data', 'softmax_label']
+net = nn.SymbolBlock.imports(symbol, input_names, params, ctx)
+net.cast(dtype)
+net.hybridize(static_alloc=True, static_shape=True)
+
+# load labels
+with open(label_file, 'r') as f:
+labels = [l.rstrip() for l in f]
+
+# load image
+img_file,_ =
urllib.request.urlretrieve('https://github.com/dmlc/web-data/blob/master/mxnet/doc/tutorials/python/predict_image/cat.jpg?raw=true')
+img = cv2.imread(img_file)
+img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
+img = cv2.resize(img, (224, 224,))
+img = np.swapaxes(img, 0, 2)
+img = np.swapaxes(img, 1, 2)
Review comment:
The error occurs while installing dependencies - Pillow and Matplotlib
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[incubator-mxnet] branch v1.x updated (0c6785f -> 6bcfce9)
This is an automated email from the ASF dual-hosted git repository. lausen pushed a change to branch v1.x in repository https://gitbox.apache.org/repos/asf/incubator-mxnet.git. from 0c6785f more support for boolean indexing and assign (#18351) add 6bcfce9 Remove manually created symbolic link to ninja-build (#18437) No new revisions were added by this update. Summary of changes: ci/docker/install/centos7_core.sh | 3 --- 1 file changed, 3 deletions(-)
[incubator-mxnet] branch v1.x updated (0c6785f -> 6bcfce9)
This is an automated email from the ASF dual-hosted git repository. lausen pushed a change to branch v1.x in repository https://gitbox.apache.org/repos/asf/incubator-mxnet.git. from 0c6785f more support for boolean indexing and assign (#18351) add 6bcfce9 Remove manually created symbolic link to ninja-build (#18437) No new revisions were added by this update. Summary of changes: ci/docker/install/centos7_core.sh | 3 --- 1 file changed, 3 deletions(-)
[incubator-mxnet] branch leezu-patch-4 updated (1c17e34 -> 1e69702)
This is an automated email from the ASF dual-hosted git repository. lausen pushed a change to branch leezu-patch-4 in repository https://gitbox.apache.org/repos/asf/incubator-mxnet.git. from 1c17e34 Disable test_CSVIter add 6ab6128 Fix flaky CSVIter test (#18390) add 0a3bdff fix true_divide (#18393) add 9c2c5d4 [numpy] Fix mean, prod with input of empty array (#18286) add b2336b6 Fix Win Environ "PATH" does not exists Bug (#18402) add 3efacd2 Add docs about default dtype (#18399) add c268462 Disable test_composite_embedding_with_one_embedding (#18383) add 83eff21 Remove references to MXNet convenience binaries on Maven (#18410) add 2806212 change _Pragma to #pragma (#18379) add 305fe07 Fix the output weight sharing in test_gluon_estimator script (#18387) add a02829e Mark test_function1 as garbage_expected (#18407) add 382279e Fix CD failure due to illegal instruction in OpenBLAS (#18408) add 5b9aedd remove mx.model.FeedForward API (#18394) add 1e69702 Merge branch 'master' into leezu-patch-4 No new revisions were added by this update. Summary of changes: contrib/clojure-package/README.md | 123 +--- .../src/_includes/get_started/linux/clojure/cpu.md | 11 - .../src/_includes/get_started/linux/clojure/gpu.md | 11 - .../src/_includes/get_started/linux/java/cpu.md| 23 +- .../src/_includes/get_started/linux/java/gpu.md| 23 +- .../src/_includes/get_started/linux/scala/cpu.md | 20 +- .../src/_includes/get_started/linux/scala/gpu.md | 22 +- .../java/docs/tutorials/mxnet_java_on_intellij.md | 188 - docs/static_site/src/pages/api/java/index.md | 4 +- .../docs/tutorials/mxnet_scala_on_intellij.md | 455 .../src/pages/get_started/build_from_source.md | 4 +- .../src/pages/get_started/java_setup.md| 135 .../static_site/src/pages/get_started/osx_setup.md | 25 +- .../src/pages/get_started/scala_setup.md | 165 - .../src/pages/get_started/ubuntu_setup.md | 20 +- example/caffe/README.md| 66 -- example/caffe/caffe_net.py | 145 example/caffe/data.py | 106 --- example/caffe/train_model.py | 109 --- example/kaggle-ndsb1/README.md | 69 -- example/kaggle-ndsb1/gen_img_list.py | 105 --- example/kaggle-ndsb1/predict_dsb.py| 70 -- example/kaggle-ndsb1/submission_dsb.py | 59 -- example/kaggle-ndsb1/symbol_dsb.py | 49 -- example/kaggle-ndsb1/train_dsb.py | 102 --- example/kaggle-ndsb1/training_curves.py| 53 -- example/kaggle-ndsb2/README.md | 6 +- example/kaggle-ndsb2/Train.py | 234 -- example/rnn/README.md | 1 - example/rnn/old/README.md | 35 - example/rnn/old/bucket_io.py | 275 example/rnn/old/char-rnn.ipynb | 549 --- example/rnn/old/get_sherlockholmes_data.sh | 43 -- example/rnn/old/gru.py | 129 example/rnn/old/gru_bucketing.py | 93 --- example/rnn/old/lstm.py| 178 - example/rnn/old/lstm_bucketing.py | 95 --- example/rnn/old/lstm_sherlockholmes.R | 123 example/rnn/old/rnn.py | 102 --- example/rnn/old/rnn_cell_demo.py | 152 example/rnn/old/rnn_model.py | 76 -- python/mxnet/libinfo.py| 2 +- python/mxnet/model.py | 784 + python/mxnet/ndarray/numpy/_op.py | 1 + python/mxnet/numpy/multiarray.py | 30 +- python/mxnet/util.py | 5 + src/io/batchify.cc | 18 +- src/operator/numpy/np_broadcast_reduce_op.h| 39 +- src/operator/numpy/np_true_divide-inl.h| 16 +- tests/nightly/dist_lenet.py| 51 -- tests/nightly/multi_lenet.py | 146 tests/python/train/test_conv.py| 98 --- tests/python/train/test_dtype.py | 69 +- tests/python/train/test_mlp.py | 115 --- tests/python/train/test_resnet_aug.py | 57 +- tests/python/unittest/test_autograd.py | 1 + tests/python/unittest/test_contrib_text.py | 6 +- tests/python/unittest/test_gluon_estimator.py | 4 +- tests/python/unittest/test_io.py | 25 +- .../python/unittest/test_numpy_interoperability.py | 2 + tools/accnn/README.md | 100 --- tools/accnn/acc_conv.py
[incubator-mxnet] branch v1.x updated (0c6785f -> 6bcfce9)
This is an automated email from the ASF dual-hosted git repository. lausen pushed a change to branch v1.x in repository https://gitbox.apache.org/repos/asf/incubator-mxnet.git. from 0c6785f more support for boolean indexing and assign (#18351) add 6bcfce9 Remove manually created symbolic link to ninja-build (#18437) No new revisions were added by this update. Summary of changes: ci/docker/install/centos7_core.sh | 3 --- 1 file changed, 3 deletions(-)
[GitHub] [incubator-mxnet] mxnet-bot commented on pull request #18432: [v1.x] Backport: Fix PyPI Packages and Python Docker Images nightly release (#18222)
mxnet-bot commented on pull request #18432: URL: https://github.com/apache/incubator-mxnet/pull/18432#issuecomment-636114503 Jenkins CI successfully triggered : [centos-cpu, centos-gpu, unix-gpu] This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[incubator-mxnet] branch leezu-patch-4 updated (1c17e34 -> 1e69702)
This is an automated email from the ASF dual-hosted git repository. lausen pushed a change to branch leezu-patch-4 in repository https://gitbox.apache.org/repos/asf/incubator-mxnet.git. from 1c17e34 Disable test_CSVIter add 6ab6128 Fix flaky CSVIter test (#18390) add 0a3bdff fix true_divide (#18393) add 9c2c5d4 [numpy] Fix mean, prod with input of empty array (#18286) add b2336b6 Fix Win Environ "PATH" does not exists Bug (#18402) add 3efacd2 Add docs about default dtype (#18399) add c268462 Disable test_composite_embedding_with_one_embedding (#18383) add 83eff21 Remove references to MXNet convenience binaries on Maven (#18410) add 2806212 change _Pragma to #pragma (#18379) add 305fe07 Fix the output weight sharing in test_gluon_estimator script (#18387) add a02829e Mark test_function1 as garbage_expected (#18407) add 382279e Fix CD failure due to illegal instruction in OpenBLAS (#18408) add 5b9aedd remove mx.model.FeedForward API (#18394) add 1e69702 Merge branch 'master' into leezu-patch-4 No new revisions were added by this update. Summary of changes: contrib/clojure-package/README.md | 123 +--- .../src/_includes/get_started/linux/clojure/cpu.md | 11 - .../src/_includes/get_started/linux/clojure/gpu.md | 11 - .../src/_includes/get_started/linux/java/cpu.md| 23 +- .../src/_includes/get_started/linux/java/gpu.md| 23 +- .../src/_includes/get_started/linux/scala/cpu.md | 20 +- .../src/_includes/get_started/linux/scala/gpu.md | 22 +- .../java/docs/tutorials/mxnet_java_on_intellij.md | 188 - docs/static_site/src/pages/api/java/index.md | 4 +- .../docs/tutorials/mxnet_scala_on_intellij.md | 455 .../src/pages/get_started/build_from_source.md | 4 +- .../src/pages/get_started/java_setup.md| 135 .../static_site/src/pages/get_started/osx_setup.md | 25 +- .../src/pages/get_started/scala_setup.md | 165 - .../src/pages/get_started/ubuntu_setup.md | 20 +- example/caffe/README.md| 66 -- example/caffe/caffe_net.py | 145 example/caffe/data.py | 106 --- example/caffe/train_model.py | 109 --- example/kaggle-ndsb1/README.md | 69 -- example/kaggle-ndsb1/gen_img_list.py | 105 --- example/kaggle-ndsb1/predict_dsb.py| 70 -- example/kaggle-ndsb1/submission_dsb.py | 59 -- example/kaggle-ndsb1/symbol_dsb.py | 49 -- example/kaggle-ndsb1/train_dsb.py | 102 --- example/kaggle-ndsb1/training_curves.py| 53 -- example/kaggle-ndsb2/README.md | 6 +- example/kaggle-ndsb2/Train.py | 234 -- example/rnn/README.md | 1 - example/rnn/old/README.md | 35 - example/rnn/old/bucket_io.py | 275 example/rnn/old/char-rnn.ipynb | 549 --- example/rnn/old/get_sherlockholmes_data.sh | 43 -- example/rnn/old/gru.py | 129 example/rnn/old/gru_bucketing.py | 93 --- example/rnn/old/lstm.py| 178 - example/rnn/old/lstm_bucketing.py | 95 --- example/rnn/old/lstm_sherlockholmes.R | 123 example/rnn/old/rnn.py | 102 --- example/rnn/old/rnn_cell_demo.py | 152 example/rnn/old/rnn_model.py | 76 -- python/mxnet/libinfo.py| 2 +- python/mxnet/model.py | 784 + python/mxnet/ndarray/numpy/_op.py | 1 + python/mxnet/numpy/multiarray.py | 30 +- python/mxnet/util.py | 5 + src/io/batchify.cc | 18 +- src/operator/numpy/np_broadcast_reduce_op.h| 39 +- src/operator/numpy/np_true_divide-inl.h| 16 +- tests/nightly/dist_lenet.py| 51 -- tests/nightly/multi_lenet.py | 146 tests/python/train/test_conv.py| 98 --- tests/python/train/test_dtype.py | 69 +- tests/python/train/test_mlp.py | 115 --- tests/python/train/test_resnet_aug.py | 57 +- tests/python/unittest/test_autograd.py | 1 + tests/python/unittest/test_contrib_text.py | 6 +- tests/python/unittest/test_gluon_estimator.py | 4 +- tests/python/unittest/test_io.py | 25 +- .../python/unittest/test_numpy_interoperability.py | 2 + tools/accnn/README.md | 100 --- tools/accnn/acc_conv.py
[incubator-mxnet] branch v1.x updated (0c6785f -> 6bcfce9)
This is an automated email from the ASF dual-hosted git repository. lausen pushed a change to branch v1.x in repository https://gitbox.apache.org/repos/asf/incubator-mxnet.git. from 0c6785f more support for boolean indexing and assign (#18351) add 6bcfce9 Remove manually created symbolic link to ninja-build (#18437) No new revisions were added by this update. Summary of changes: ci/docker/install/centos7_core.sh | 3 --- 1 file changed, 3 deletions(-)
[GitHub] [incubator-mxnet] zhreshold commented on a change in pull request #18434: add image classification tutorial for jetson
zhreshold commented on a change in pull request #18434:
URL: https://github.com/apache/incubator-mxnet/pull/18434#discussion_r432657159
##
File path:
docs/python_docs/python/tutorials/deploy/inference/image_classification_jetson.md
##
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+# Image Classication using pretrained ResNet-50 model on Jetson module
+
+This tutorial shows how to install latest MXNet v1.6 with Jetson support and
use it to deploy a pre-trained MXNet model for image classification on a Jetson
module.
+
+## What's in this tutorial?
+
+This tutorial shows how to:
+
+1. Install MXNet v1.6 with Jetson support along with its dependencies
+
+2. Deploy a pre-trained MXNet model for image classifcation on a Jetson module
+
+### Who's this tutorial for?
+
+This tutorial would benefit developers working on any Jetson module
implementing a deep learning application. It assumes that readers have a Jetson
module setup, are familiar with the Jetson working environment and are somewhat
familiar with deep learning using MXNet.
+
+### How to use this tutorial?
+
+To follow this tutorial, you need to setup a [Jetson
module](https://developer.nvidia.com/embedded/develop/hardware) and install
latest [Jetpack 4.4](https://docs.nvidia.com/jetson/jetpack/release-notes/)
using NVIDIA [SDK manager](https://developer.nvidia.com/nvidia-sdk-manager).
+
+All instructions described in this tutorial can be executed on the any Jetson
module directly or via SSH.
+
+## Prerequisites
+
+To complete this tutorial, you will need:
+
+* A Jetson module with Jetpack 4.4 installed
+* [Swapfile](https://help.ubuntu.com/community/SwapFaq) installed (in case of
Jetson Nano) for additional memory
+
+## Installing MXNet v1.6 with Jetson support
+
+We start by installing MXNet dependencies
+```bash
+sudo apt-get update
+sudo apt-get install -y git build-essential libopenblas-dev libopencv-dev
python3-pip
+sudo pip3 install -U pip
+```
+
+Then we download and install MXNet v1.6 wheel with Jetson support
+```bash
+wget
https://mxnet-public.s3.us-east-2.amazonaws.com/install/jetson/1.6.0/mxnet_cu102-1.6.0-py2.py3-none-linux_aarch64.whl
+sudo pip3 install mxnet_cu102-1.6.0-py2.py3-none-linux_aarch64.whl
+```
+
+And we are done. You can test the installation now by importing mxnet from
python3
+```bash
+>>> python3 -c 'import mxnet'
+```
+
+## Running a pre-trained ResNet-50 model on Jetson
+
+We are now ready to run a pre-trained model and run inference on a Jetson
module. In this tutorial we are using ResNet-50 model trained on Imagenet
dataset. We run the following classification script with either cpu/gpu context
using python3.
+
+```python
+from mxnet.gluon import nn
+import mxnet as mx
+import numpy as np
+import urllib.request
+import cv2
+
+# set context
+ctx = mx.gpu()
+dtype = 'float32'
+bsize = 1
+
+# download model files
+path = 'http://data.mxnet.io/models/imagenet/'
+symbol,_ =
urllib.request.urlretrieve(path+'resnet/50-layers/resnet-50-symbol.json')
+params,_ =
urllib.request.urlretrieve(path+'resnet/50-layers/resnet-50-.params')
+label_file,_ = urllib.request.urlretrieve(path+'synset.txt')
+
+# load model
+input_names = ['data', 'softmax_label']
+net = nn.SymbolBlock.imports(symbol, input_names, params, ctx)
+net.cast(dtype)
+net.hybridize(static_alloc=True, static_shape=True)
+
+# load labels
+with open(label_file, 'r') as f:
+labels = [l.rstrip() for l in f]
+
+# load image
+img_file,_ =
urllib.request.urlretrieve('https://github.com/dmlc/web-data/blob/master/mxnet/doc/tutorials/python/predict_image/cat.jpg?raw=true')
+img = cv2.imread(img_file)
+img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
+img = cv2.resize(img, (224, 224,))
+img = np.swapaxes(img, 0, 2)
+img = np.swapaxes(img, 1, 2)
Review comment:
What's the installation error using `pip`?
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[GitHub] [incubator-mxnet] leezu commented on pull request #18432: [v1.x] Backport: Fix PyPI Packages and Python Docker Images nightly release (#18222)
leezu commented on pull request #18432: URL: https://github.com/apache/incubator-mxnet/pull/18432#issuecomment-636114447 @mxnet-bot run ci [centos-cpu, centos-gpu, unix-gpu] This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[GitHub] [incubator-mxnet] leezu edited a comment on issue #18244: unix-cpu MKL/MKL-DNN Test Time
leezu edited a comment on issue #18244: URL: https://github.com/apache/incubator-mxnet/issues/18244#issuecomment-636114038 Thank you for looking into this! Do you have any insights into why this only affects MKL builds? This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[GitHub] [incubator-mxnet] leezu commented on issue #18244: unix-cpu MKL/MKL-DNN Test Time
leezu commented on issue #18244: URL: https://github.com/apache/incubator-mxnet/issues/18244#issuecomment-636114038 Do you have any insights into why this only affects MKL builds? This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[incubator-mxnet] branch leezu-patch-4 updated (1c17e34 -> 1e69702)
This is an automated email from the ASF dual-hosted git repository. lausen pushed a change to branch leezu-patch-4 in repository https://gitbox.apache.org/repos/asf/incubator-mxnet.git. from 1c17e34 Disable test_CSVIter add 6ab6128 Fix flaky CSVIter test (#18390) add 0a3bdff fix true_divide (#18393) add 9c2c5d4 [numpy] Fix mean, prod with input of empty array (#18286) add b2336b6 Fix Win Environ "PATH" does not exists Bug (#18402) add 3efacd2 Add docs about default dtype (#18399) add c268462 Disable test_composite_embedding_with_one_embedding (#18383) add 83eff21 Remove references to MXNet convenience binaries on Maven (#18410) add 2806212 change _Pragma to #pragma (#18379) add 305fe07 Fix the output weight sharing in test_gluon_estimator script (#18387) add a02829e Mark test_function1 as garbage_expected (#18407) add 382279e Fix CD failure due to illegal instruction in OpenBLAS (#18408) add 5b9aedd remove mx.model.FeedForward API (#18394) add 1e69702 Merge branch 'master' into leezu-patch-4 No new revisions were added by this update. Summary of changes: contrib/clojure-package/README.md | 123 +--- .../src/_includes/get_started/linux/clojure/cpu.md | 11 - .../src/_includes/get_started/linux/clojure/gpu.md | 11 - .../src/_includes/get_started/linux/java/cpu.md| 23 +- .../src/_includes/get_started/linux/java/gpu.md| 23 +- .../src/_includes/get_started/linux/scala/cpu.md | 20 +- .../src/_includes/get_started/linux/scala/gpu.md | 22 +- .../java/docs/tutorials/mxnet_java_on_intellij.md | 188 - docs/static_site/src/pages/api/java/index.md | 4 +- .../docs/tutorials/mxnet_scala_on_intellij.md | 455 .../src/pages/get_started/build_from_source.md | 4 +- .../src/pages/get_started/java_setup.md| 135 .../static_site/src/pages/get_started/osx_setup.md | 25 +- .../src/pages/get_started/scala_setup.md | 165 - .../src/pages/get_started/ubuntu_setup.md | 20 +- example/caffe/README.md| 66 -- example/caffe/caffe_net.py | 145 example/caffe/data.py | 106 --- example/caffe/train_model.py | 109 --- example/kaggle-ndsb1/README.md | 69 -- example/kaggle-ndsb1/gen_img_list.py | 105 --- example/kaggle-ndsb1/predict_dsb.py| 70 -- example/kaggle-ndsb1/submission_dsb.py | 59 -- example/kaggle-ndsb1/symbol_dsb.py | 49 -- example/kaggle-ndsb1/train_dsb.py | 102 --- example/kaggle-ndsb1/training_curves.py| 53 -- example/kaggle-ndsb2/README.md | 6 +- example/kaggle-ndsb2/Train.py | 234 -- example/rnn/README.md | 1 - example/rnn/old/README.md | 35 - example/rnn/old/bucket_io.py | 275 example/rnn/old/char-rnn.ipynb | 549 --- example/rnn/old/get_sherlockholmes_data.sh | 43 -- example/rnn/old/gru.py | 129 example/rnn/old/gru_bucketing.py | 93 --- example/rnn/old/lstm.py| 178 - example/rnn/old/lstm_bucketing.py | 95 --- example/rnn/old/lstm_sherlockholmes.R | 123 example/rnn/old/rnn.py | 102 --- example/rnn/old/rnn_cell_demo.py | 152 example/rnn/old/rnn_model.py | 76 -- python/mxnet/libinfo.py| 2 +- python/mxnet/model.py | 784 + python/mxnet/ndarray/numpy/_op.py | 1 + python/mxnet/numpy/multiarray.py | 30 +- python/mxnet/util.py | 5 + src/io/batchify.cc | 18 +- src/operator/numpy/np_broadcast_reduce_op.h| 39 +- src/operator/numpy/np_true_divide-inl.h| 16 +- tests/nightly/dist_lenet.py| 51 -- tests/nightly/multi_lenet.py | 146 tests/python/train/test_conv.py| 98 --- tests/python/train/test_dtype.py | 69 +- tests/python/train/test_mlp.py | 115 --- tests/python/train/test_resnet_aug.py | 57 +- tests/python/unittest/test_autograd.py | 1 + tests/python/unittest/test_contrib_text.py | 6 +- tests/python/unittest/test_gluon_estimator.py | 4 +- tests/python/unittest/test_io.py | 25 +- .../python/unittest/test_numpy_interoperability.py | 2 + tools/accnn/README.md | 100 --- tools/accnn/acc_conv.py
[incubator-mxnet] branch v1.x updated (0c6785f -> 6bcfce9)
This is an automated email from the ASF dual-hosted git repository. lausen pushed a change to branch v1.x in repository https://gitbox.apache.org/repos/asf/incubator-mxnet.git. from 0c6785f more support for boolean indexing and assign (#18351) add 6bcfce9 Remove manually created symbolic link to ninja-build (#18437) No new revisions were added by this update. Summary of changes: ci/docker/install/centos7_core.sh | 3 --- 1 file changed, 3 deletions(-)
[incubator-mxnet] branch leezu-patch-4 updated (1c17e34 -> 1e69702)
This is an automated email from the ASF dual-hosted git repository. lausen pushed a change to branch leezu-patch-4 in repository https://gitbox.apache.org/repos/asf/incubator-mxnet.git. from 1c17e34 Disable test_CSVIter add 6ab6128 Fix flaky CSVIter test (#18390) add 0a3bdff fix true_divide (#18393) add 9c2c5d4 [numpy] Fix mean, prod with input of empty array (#18286) add b2336b6 Fix Win Environ "PATH" does not exists Bug (#18402) add 3efacd2 Add docs about default dtype (#18399) add c268462 Disable test_composite_embedding_with_one_embedding (#18383) add 83eff21 Remove references to MXNet convenience binaries on Maven (#18410) add 2806212 change _Pragma to #pragma (#18379) add 305fe07 Fix the output weight sharing in test_gluon_estimator script (#18387) add a02829e Mark test_function1 as garbage_expected (#18407) add 382279e Fix CD failure due to illegal instruction in OpenBLAS (#18408) add 5b9aedd remove mx.model.FeedForward API (#18394) add 1e69702 Merge branch 'master' into leezu-patch-4 No new revisions were added by this update. Summary of changes: contrib/clojure-package/README.md | 123 +--- .../src/_includes/get_started/linux/clojure/cpu.md | 11 - .../src/_includes/get_started/linux/clojure/gpu.md | 11 - .../src/_includes/get_started/linux/java/cpu.md| 23 +- .../src/_includes/get_started/linux/java/gpu.md| 23 +- .../src/_includes/get_started/linux/scala/cpu.md | 20 +- .../src/_includes/get_started/linux/scala/gpu.md | 22 +- .../java/docs/tutorials/mxnet_java_on_intellij.md | 188 - docs/static_site/src/pages/api/java/index.md | 4 +- .../docs/tutorials/mxnet_scala_on_intellij.md | 455 .../src/pages/get_started/build_from_source.md | 4 +- .../src/pages/get_started/java_setup.md| 135 .../static_site/src/pages/get_started/osx_setup.md | 25 +- .../src/pages/get_started/scala_setup.md | 165 - .../src/pages/get_started/ubuntu_setup.md | 20 +- example/caffe/README.md| 66 -- example/caffe/caffe_net.py | 145 example/caffe/data.py | 106 --- example/caffe/train_model.py | 109 --- example/kaggle-ndsb1/README.md | 69 -- example/kaggle-ndsb1/gen_img_list.py | 105 --- example/kaggle-ndsb1/predict_dsb.py| 70 -- example/kaggle-ndsb1/submission_dsb.py | 59 -- example/kaggle-ndsb1/symbol_dsb.py | 49 -- example/kaggle-ndsb1/train_dsb.py | 102 --- example/kaggle-ndsb1/training_curves.py| 53 -- example/kaggle-ndsb2/README.md | 6 +- example/kaggle-ndsb2/Train.py | 234 -- example/rnn/README.md | 1 - example/rnn/old/README.md | 35 - example/rnn/old/bucket_io.py | 275 example/rnn/old/char-rnn.ipynb | 549 --- example/rnn/old/get_sherlockholmes_data.sh | 43 -- example/rnn/old/gru.py | 129 example/rnn/old/gru_bucketing.py | 93 --- example/rnn/old/lstm.py| 178 - example/rnn/old/lstm_bucketing.py | 95 --- example/rnn/old/lstm_sherlockholmes.R | 123 example/rnn/old/rnn.py | 102 --- example/rnn/old/rnn_cell_demo.py | 152 example/rnn/old/rnn_model.py | 76 -- python/mxnet/libinfo.py| 2 +- python/mxnet/model.py | 784 + python/mxnet/ndarray/numpy/_op.py | 1 + python/mxnet/numpy/multiarray.py | 30 +- python/mxnet/util.py | 5 + src/io/batchify.cc | 18 +- src/operator/numpy/np_broadcast_reduce_op.h| 39 +- src/operator/numpy/np_true_divide-inl.h| 16 +- tests/nightly/dist_lenet.py| 51 -- tests/nightly/multi_lenet.py | 146 tests/python/train/test_conv.py| 98 --- tests/python/train/test_dtype.py | 69 +- tests/python/train/test_mlp.py | 115 --- tests/python/train/test_resnet_aug.py | 57 +- tests/python/unittest/test_autograd.py | 1 + tests/python/unittest/test_contrib_text.py | 6 +- tests/python/unittest/test_gluon_estimator.py | 4 +- tests/python/unittest/test_io.py | 25 +- .../python/unittest/test_numpy_interoperability.py | 2 + tools/accnn/README.md | 100 --- tools/accnn/acc_conv.py
[GitHub] [incubator-mxnet] leezu merged pull request #18437: [v1.x] Fix CI: Remove manually created symbolic link to ninja-build in CentOS pipelines
leezu merged pull request #18437: URL: https://github.com/apache/incubator-mxnet/pull/18437 This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[incubator-mxnet] branch leezu-patch-4 updated (1c17e34 -> 1e69702)
This is an automated email from the ASF dual-hosted git repository. lausen pushed a change to branch leezu-patch-4 in repository https://gitbox.apache.org/repos/asf/incubator-mxnet.git. from 1c17e34 Disable test_CSVIter add 6ab6128 Fix flaky CSVIter test (#18390) add 0a3bdff fix true_divide (#18393) add 9c2c5d4 [numpy] Fix mean, prod with input of empty array (#18286) add b2336b6 Fix Win Environ "PATH" does not exists Bug (#18402) add 3efacd2 Add docs about default dtype (#18399) add c268462 Disable test_composite_embedding_with_one_embedding (#18383) add 83eff21 Remove references to MXNet convenience binaries on Maven (#18410) add 2806212 change _Pragma to #pragma (#18379) add 305fe07 Fix the output weight sharing in test_gluon_estimator script (#18387) add a02829e Mark test_function1 as garbage_expected (#18407) add 382279e Fix CD failure due to illegal instruction in OpenBLAS (#18408) add 5b9aedd remove mx.model.FeedForward API (#18394) add 1e69702 Merge branch 'master' into leezu-patch-4 No new revisions were added by this update. Summary of changes: contrib/clojure-package/README.md | 123 +--- .../src/_includes/get_started/linux/clojure/cpu.md | 11 - .../src/_includes/get_started/linux/clojure/gpu.md | 11 - .../src/_includes/get_started/linux/java/cpu.md| 23 +- .../src/_includes/get_started/linux/java/gpu.md| 23 +- .../src/_includes/get_started/linux/scala/cpu.md | 20 +- .../src/_includes/get_started/linux/scala/gpu.md | 22 +- .../java/docs/tutorials/mxnet_java_on_intellij.md | 188 - docs/static_site/src/pages/api/java/index.md | 4 +- .../docs/tutorials/mxnet_scala_on_intellij.md | 455 .../src/pages/get_started/build_from_source.md | 4 +- .../src/pages/get_started/java_setup.md| 135 .../static_site/src/pages/get_started/osx_setup.md | 25 +- .../src/pages/get_started/scala_setup.md | 165 - .../src/pages/get_started/ubuntu_setup.md | 20 +- example/caffe/README.md| 66 -- example/caffe/caffe_net.py | 145 example/caffe/data.py | 106 --- example/caffe/train_model.py | 109 --- example/kaggle-ndsb1/README.md | 69 -- example/kaggle-ndsb1/gen_img_list.py | 105 --- example/kaggle-ndsb1/predict_dsb.py| 70 -- example/kaggle-ndsb1/submission_dsb.py | 59 -- example/kaggle-ndsb1/symbol_dsb.py | 49 -- example/kaggle-ndsb1/train_dsb.py | 102 --- example/kaggle-ndsb1/training_curves.py| 53 -- example/kaggle-ndsb2/README.md | 6 +- example/kaggle-ndsb2/Train.py | 234 -- example/rnn/README.md | 1 - example/rnn/old/README.md | 35 - example/rnn/old/bucket_io.py | 275 example/rnn/old/char-rnn.ipynb | 549 --- example/rnn/old/get_sherlockholmes_data.sh | 43 -- example/rnn/old/gru.py | 129 example/rnn/old/gru_bucketing.py | 93 --- example/rnn/old/lstm.py| 178 - example/rnn/old/lstm_bucketing.py | 95 --- example/rnn/old/lstm_sherlockholmes.R | 123 example/rnn/old/rnn.py | 102 --- example/rnn/old/rnn_cell_demo.py | 152 example/rnn/old/rnn_model.py | 76 -- python/mxnet/libinfo.py| 2 +- python/mxnet/model.py | 784 + python/mxnet/ndarray/numpy/_op.py | 1 + python/mxnet/numpy/multiarray.py | 30 +- python/mxnet/util.py | 5 + src/io/batchify.cc | 18 +- src/operator/numpy/np_broadcast_reduce_op.h| 39 +- src/operator/numpy/np_true_divide-inl.h| 16 +- tests/nightly/dist_lenet.py| 51 -- tests/nightly/multi_lenet.py | 146 tests/python/train/test_conv.py| 98 --- tests/python/train/test_dtype.py | 69 +- tests/python/train/test_mlp.py | 115 --- tests/python/train/test_resnet_aug.py | 57 +- tests/python/unittest/test_autograd.py | 1 + tests/python/unittest/test_contrib_text.py | 6 +- tests/python/unittest/test_gluon_estimator.py | 4 +- tests/python/unittest/test_io.py | 25 +- .../python/unittest/test_numpy_interoperability.py | 2 + tools/accnn/README.md | 100 --- tools/accnn/acc_conv.py
[GitHub] [incubator-mxnet] mseth10 commented on a change in pull request #18434: add image classification tutorial for jetson
mseth10 commented on a change in pull request #18434:
URL: https://github.com/apache/incubator-mxnet/pull/18434#discussion_r432652855
##
File path:
docs/python_docs/python/tutorials/deploy/inference/image_classification_jetson.md
##
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+# Image Classication using pretrained ResNet-50 model on Jetson module
+
+This tutorial shows how to install latest MXNet v1.6 with Jetson support and
use it to deploy a pre-trained MXNet model for image classification on a Jetson
module.
+
+## What's in this tutorial?
+
+This tutorial shows how to:
+
+1. Install MXNet v1.6 with Jetson support along with its dependencies
+
+2. Deploy a pre-trained MXNet model for image classifcation on a Jetson module
+
+### Who's this tutorial for?
+
+This tutorial would benefit developers working on any Jetson module
implementing a deep learning application. It assumes that readers have a Jetson
module setup, are familiar with the Jetson working environment and are somewhat
familiar with deep learning using MXNet.
+
+### How to use this tutorial?
+
+To follow this tutorial, you need to setup a [Jetson
module](https://developer.nvidia.com/embedded/develop/hardware) and install
latest [Jetpack 4.4](https://docs.nvidia.com/jetson/jetpack/release-notes/)
using NVIDIA [SDK manager](https://developer.nvidia.com/nvidia-sdk-manager).
+
+All instructions described in this tutorial can be executed on the any Jetson
module directly or via SSH.
+
+## Prerequisites
+
+To complete this tutorial, you will need:
+
+* A Jetson module with Jetpack 4.4 installed
+* [Swapfile](https://help.ubuntu.com/community/SwapFaq) installed (in case of
Jetson Nano) for additional memory
+
+## Installing MXNet v1.6 with Jetson support
+
+We start by installing MXNet dependencies
+```bash
+sudo apt-get update
+sudo apt-get install -y git build-essential libopenblas-dev libopencv-dev
python3-pip
+sudo pip3 install -U pip
+```
+
+Then we download and install MXNet v1.6 wheel with Jetson support
+```bash
+wget
https://mxnet-public.s3.us-east-2.amazonaws.com/install/jetson/1.6.0/mxnet_cu102-1.6.0-py2.py3-none-linux_aarch64.whl
+sudo pip3 install mxnet_cu102-1.6.0-py2.py3-none-linux_aarch64.whl
+```
+
+And we are done. You can test the installation now by importing mxnet from
python3
+```bash
+>>> python3 -c 'import mxnet'
+```
+
+## Running a pre-trained ResNet-50 model on Jetson
+
+We are now ready to run a pre-trained model and run inference on a Jetson
module. In this tutorial we are using ResNet-50 model trained on Imagenet
dataset. We run the following classification script with either cpu/gpu context
using python3.
+
+```python
+from mxnet.gluon import nn
+import mxnet as mx
+import numpy as np
+import urllib.request
+import cv2
+
+# set context
+ctx = mx.gpu()
+dtype = 'float32'
+bsize = 1
+
+# download model files
+path = 'http://data.mxnet.io/models/imagenet/'
+symbol,_ =
urllib.request.urlretrieve(path+'resnet/50-layers/resnet-50-symbol.json')
+params,_ =
urllib.request.urlretrieve(path+'resnet/50-layers/resnet-50-.params')
+label_file,_ = urllib.request.urlretrieve(path+'synset.txt')
+
+# load model
+input_names = ['data', 'softmax_label']
+net = nn.SymbolBlock.imports(symbol, input_names, params, ctx)
+net.cast(dtype)
+net.hybridize(static_alloc=True, static_shape=True)
+
+# load labels
+with open(label_file, 'r') as f:
+labels = [l.rstrip() for l in f]
+
+# load image
+img_file,_ =
urllib.request.urlretrieve('https://github.com/dmlc/web-data/blob/master/mxnet/doc/tutorials/python/predict_image/cat.jpg?raw=true')
+img = cv2.imread(img_file)
+img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
+img = cv2.resize(img, (224, 224,))
+img = np.swapaxes(img, 0, 2)
+img = np.swapaxes(img, 1, 2)
+
+# format input
+batch = mx.nd.zeros((bsize,) + img.shape)
+for i in range(bsize):
+batch[i] = img
+inputs = batch.astype(dtype)
+mx_img = [mx.nd.array(inputs,ctx), mx.nd.zeros((bsize,),ctx)]
+
+# infer
+results = net(*mx_img)
+prob = results[0].asnumpy()
+prob = np.squeeze(prob)
+a = np.argsort(prob)[::-1]
+for i in a[0:5]:
+print('probability=%f, class=%s' %(prob[i], labels[i]))
+```
+
+After running the above script, you should get the following output showing
the five classes that the image most relates to with probability:
+```bash
+probability=0.418679, class=n02119789 kit fox, Vulpes macrotis
+probability=0.293494, class=n02119022 red fox, Vulpes vulpes
+probability=0.029321, class=n02120505 grey fox, gray fox, Urocyon
cinereoargenteus
+probability=0.026230, class=n02124075 Egyptian cat
+probability=0.022557, class=n02085620 Chihuahua
+```
Review comment:
That's a good idea. But I am not targeting performance analysis in this
particular tutorial. Will put up another tutorial for performance after testing
on more modules.
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[incubator-mxnet] branch leezu-patch-4 created (now 1c17e34)
This is an automated email from the ASF dual-hosted git repository. lausen pushed a change to branch leezu-patch-4 in repository https://gitbox.apache.org/repos/asf/incubator-mxnet.git. at 1c17e34 Disable test_CSVIter No new revisions were added by this update.
[GitHub] [incubator-mxnet] leezu commented on pull request #18391: Disable test_CSVIter
leezu commented on pull request #18391: URL: https://github.com/apache/incubator-mxnet/pull/18391#issuecomment-636109819 @mxnet-bot run ci [all] This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[incubator-mxnet] branch leezu-patch-4 created (now 1c17e34)
This is an automated email from the ASF dual-hosted git repository. lausen pushed a change to branch leezu-patch-4 in repository https://gitbox.apache.org/repos/asf/incubator-mxnet.git. at 1c17e34 Disable test_CSVIter No new revisions were added by this update.
